1 Summary statistics per sample

1.1 Raw data lottery choices (cf. Table 1 in main text)

The following tables provide the raw data for the three multiple prices lists (with monotonous switching) by countries. BJR2014 denotes the original study. Note that in the sample from the Netherlands, a few respondents have stopped the survey after the the first and second multiple prices lists. We used these data in the structural models, but not in the mid-point approach.

1.1.1 Series 1

Series No Country Total
BJR2014 Austria Croatia France_I France_II Germany Italy Netherlands Poland Slovenia Spain Sweden
0 16
15 % 		22
17.2 % 		13
12.5 % 		18
18.8 % 		4
14.3 % 		16
10.5 % 		31
23.8 % 		27
16.9 % 		22
13 % 		18
15.8 % 		41
31.5 % 		42
19.3 % 		270
17.6 %
1 3
2.8 % 		2
1.6 % 		2
1.9 % 		4
4.2 % 		2
7.1 % 		1
0.7 % 		0
0 % 		1
0.6 % 		3
1.8 % 		2
1.8 % 		3
2.3 % 		1
0.5 % 		24
1.6 %
2 1
0.9 % 		9
7 % 		2
1.9 % 		2
2.1 % 		0
0 % 		7
4.6 % 		5
3.8 % 		7
4.4 % 		5
3 % 		3
2.6 % 		2
1.5 % 		10
4.6 % 		53
3.4 %
3 0
0 % 		8
6.2 % 		9
8.7 % 		6
6.2 % 		1
3.6 % 		11
7.2 % 		12
9.2 % 		7
4.4 % 		8
4.7 % 		8
7 % 		7
5.4 % 		15
6.9 % 		92
6 %
4 3
2.8 % 		11
8.6 % 		7
6.7 % 		4
4.2 % 		4
14.3 % 		22
14.4 % 		16
12.3 % 		11
6.9 % 		16
9.5 % 		6
5.3 % 		14
10.8 % 		9
4.1 % 		123
8 %
5 8
7.5 % 		23
18 % 		16
15.4 % 		14
14.6 % 		4
14.3 % 		18
11.8 % 		15
11.5 % 		23
14.4 % 		22
13 % 		14
12.3 % 		10
7.7 % 		23
10.6 % 		190
12.4 %
6 15
14 % 		11
8.6 % 		11
10.6 % 		15
15.6 % 		4
14.3 % 		23
15 % 		8
6.2 % 		25
15.6 % 		19
11.2 % 		14
12.3 % 		10
7.7 % 		28
12.8 % 		183
11.9 %
7 2
1.9 % 		12
9.4 % 		9
8.7 % 		7
7.3 % 		0
0 % 		14
9.2 % 		10
7.7 % 		9
5.6 % 		15
8.9 % 		9
7.9 % 		10
7.7 % 		16
7.3 % 		113
7.4 %
8 5
4.7 % 		4
3.1 % 		6
5.8 % 		8
8.3 % 		0
0 % 		13
8.5 % 		8
6.2 % 		11
6.9 % 		8
4.7 % 		12
10.5 % 		5
3.8 % 		16
7.3 % 		96
6.2 %
9 9
8.4 % 		0
0 % 		5
4.8 % 		5
5.2 % 		3
10.7 % 		3
2 % 		6
4.6 % 		8
5 % 		8
4.7 % 		11
9.6 % 		3
2.3 % 		17
7.8 % 		78
5.1 %
10 2
1.9 % 		8
6.2 % 		10
9.6 % 		4
4.2 % 		1
3.6 % 		7
4.6 % 		1
0.8 % 		3
1.9 % 		7
4.1 % 		6
5.3 % 		5
3.8 % 		12
5.5 % 		66
4.3 %
11 2
1.9 % 		7
5.5 % 		2
1.9 % 		1
1 % 		1
3.6 % 		6
3.9 % 		2
1.5 % 		6
3.8 % 		4
2.4 % 		5
4.4 % 		5
3.8 % 		4
1.8 % 		45
2.9 %
12 41
38.3 % 		11
8.6 % 		12
11.5 % 		8
8.3 % 		4
14.3 % 		12
7.8 % 		16
12.3 % 		22
13.8 % 		32
18.9 % 		6
5.3 % 		15
11.5 % 		25
11.5 % 		204
13.3 %
Total 107
100 % 		128
100 % 		104
100 % 		96
100 % 		28
100 % 		153
100 % 		130
100 % 		160
100 % 		169
100 % 		114
100 % 		130
100 % 		218
100 % 		1537
100 %






1.1.2 Series 2

Series No Country Total
BJR2014 Austria Croatia France_I France_II Germany Italy Netherlands Poland Slovenia Spain Sweden
0 28
26.2 % 		37
28.9 % 		18
17.3 % 		31
32.3 % 		9
32.1 % 		33
21.6 % 		34
26.2 % 		48
31 % 		38
22.5 % 		18
15.8 % 		36
27.7 % 		49
22.5 % 		379
24.7 %
1 2
1.9 % 		0
0 % 		2
1.9 % 		2
2.1 % 		0
0 % 		3
2 % 		5
3.8 % 		1
0.6 % 		1
0.6 % 		2
1.8 % 		0
0 % 		1
0.5 % 		19
1.2 %
2 1
0.9 % 		5
3.9 % 		1
1 % 		2
2.1 % 		1
3.6 % 		3
2 % 		4
3.1 % 		4
2.6 % 		1
0.6 % 		4
3.5 % 		2
1.5 % 		3
1.4 % 		31
2 %
3 0
0 % 		6
4.7 % 		11
10.6 % 		2
2.1 % 		1
3.6 % 		11
7.2 % 		5
3.8 % 		6
3.9 % 		5
3 % 		5
4.4 % 		2
1.5 % 		13
6 % 		67
4.4 %
4 3
2.8 % 		10
7.8 % 		3
2.9 % 		3
3.1 % 		0
0 % 		9
5.9 % 		4
3.1 % 		4
2.6 % 		8
4.7 % 		7
6.1 % 		12
9.2 % 		7
3.2 % 		70
4.6 %
5 2
1.9 % 		7
5.5 % 		11
10.6 % 		5
5.2 % 		0
0 % 		10
6.5 % 		9
6.9 % 		5
3.2 % 		9
5.3 % 		15
13.2 % 		5
3.8 % 		9
4.1 % 		87
5.7 %
6 3
2.8 % 		17
13.3 % 		3
2.9 % 		3
3.1 % 		1
3.6 % 		8
5.2 % 		8
6.2 % 		10
6.5 % 		13
7.7 % 		3
2.6 % 		7
5.4 % 		7
3.2 % 		83
5.4 %
7 9
8.4 % 		6
4.7 % 		5
4.8 % 		10
10.4 % 		1
3.6 % 		6
3.9 % 		8
6.2 % 		11
7.1 % 		15
8.9 % 		6
5.3 % 		8
6.2 % 		11
5 % 		96
6.3 %
8 5
4.7 % 		11
8.6 % 		3
2.9 % 		7
7.3 % 		2
7.1 % 		4
2.6 % 		3
2.3 % 		7
4.5 % 		8
4.7 % 		5
4.4 % 		5
3.8 % 		5
2.3 % 		65
4.2 %
9 4
3.7 % 		4
3.1 % 		5
4.8 % 		1
1 % 		2
7.1 % 		5
3.3 % 		4
3.1 % 		4
2.6 % 		7
4.1 % 		8
7 % 		8
6.2 % 		12
5.5 % 		64
4.2 %
10 3
2.8 % 		5
3.9 % 		12
11.5 % 		6
6.2 % 		1
3.6 % 		9
5.9 % 		13
10 % 		16
10.3 % 		6
3.6 % 		15
13.2 % 		3
2.3 % 		19
8.7 % 		108
7 %
11 7
6.5 % 		11
8.6 % 		7
6.7 % 		4
4.2 % 		4
14.3 % 		12
7.8 % 		10
7.7 % 		9
5.8 % 		14
8.3 % 		4
3.5 % 		5
3.8 % 		27
12.4 % 		114
7.4 %
12 0
0 % 		1
0.8 % 		6
5.8 % 		5
5.2 % 		1
3.6 % 		8
5.2 % 		5
3.8 % 		4
2.6 % 		8
4.7 % 		5
4.4 % 		13
10 % 		9
4.1 % 		65
4.2 %
13 5
4.7 % 		1
0.8 % 		1
1 % 		1
1 % 		1
3.6 % 		5
3.3 % 		3
2.3 % 		1
0.6 % 		6
3.6 % 		2
1.8 % 		6
4.6 % 		7
3.2 % 		39
2.5 %
14 35
32.7 % 		7
5.5 % 		16
15.4 % 		14
14.6 % 		4
14.3 % 		27
17.6 % 		15
11.5 % 		25
16.1 % 		30
17.8 % 		15
13.2 % 		18
13.8 % 		39
17.9 % 		245
16 %
Total 107
100 % 		128
100 % 		104
100 % 		96
100 % 		28
100 % 		153
100 % 		130
100 % 		155
100 % 		169
100 % 		114
100 % 		130
100 % 		218
100 % 		1532
100 %






1.1.3 Series 3

Series No Country Total
BJR2014 Austria Croatia France_I France_II Germany Italy Netherlands Poland Slovenia Spain Sweden
0 11
10.3 % 		18
14.1 % 		12
11.5 % 		18
18.8 % 		4
14.3 % 		22
14.4 % 		32
24.6 % 		24
15.6 % 		36
21.3 % 		22
19.3 % 		16
12.3 % 		39
17.9 % 		254
16.6 %
1 8
7.5 % 		29
22.7 % 		19
18.3 % 		22
22.9 % 		8
28.6 % 		35
22.9 % 		22
16.9 % 		63
40.9 % 		23
13.6 % 		14
12.3 % 		16
12.3 % 		76
34.9 % 		335
21.9 %
2 15
14 % 		32
25 % 		21
20.2 % 		8
8.3 % 		3
10.7 % 		28
18.3 % 		16
12.3 % 		20
13 % 		16
9.5 % 		16
14 % 		17
13.1 % 		21
9.6 % 		213
13.9 %
3 14
13.1 % 		12
9.4 % 		9
8.7 % 		8
8.3 % 		2
7.1 % 		22
14.4 % 		22
16.9 % 		11
7.1 % 		17
10.1 % 		8
7 % 		14
10.8 % 		18
8.3 % 		157
10.3 %
4 26
24.3 % 		17
13.3 % 		16
15.4 % 		16
16.7 % 		3
10.7 % 		23
15 % 		13
10 % 		15
9.7 % 		34
20.1 % 		22
19.3 % 		29
22.3 % 		36
16.5 % 		250
16.3 %
5 5
4.7 % 		5
3.9 % 		12
11.5 % 		5
5.2 % 		0
0 % 		8
5.2 % 		6
4.6 % 		3
1.9 % 		6
3.6 % 		8
7 % 		13
10 % 		10
4.6 % 		81
5.3 %
6 4
3.7 % 		4
3.1 % 		6
5.8 % 		1
1 % 		1
3.6 % 		1
0.7 % 		7
5.4 % 		5
3.2 % 		5
3 % 		2
1.8 % 		9
6.9 % 		6
2.8 % 		51
3.3 %
7 24
22.4 % 		11
8.6 % 		9
8.7 % 		18
18.8 % 		7
25 % 		14
9.2 % 		12
9.2 % 		13
8.4 % 		32
18.9 % 		22
19.3 % 		16
12.3 % 		12
5.5 % 		190
12.4 %
Total 107
100 % 		128
100 % 		104
100 % 		96
100 % 		28
100 % 		153
100 % 		130
100 % 		154
100 % 		169
100 % 		114
100 % 		130
100 % 		218
100 % 		1531
100 %






1.2 Summary statistics for socio-demographic variables by sample

The following table presents, in short form, the number of observations, number of missing observations, mean, and median for each of the samples.

1.2.1 Socio-demographics by sample

Country
N
Age
NbChildren
EducSup
Trust
Farmsize
LandOwned
IndivOwnder
Age of the subject (years)
Number of children in the household
Dummy if education level beyond secondary school
Dummy if self-reported as trusting other people
Total arable area in 100 ha
Proportion of land out of the arable area which is owned

Dummy if the farm is a sole proprietorship or a society with only one associate

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD
BJR2014 107 45.77 9.34 1.23 1.15 0.34 0.47 0.25 0.44 1.94 1.03 0.30 0.21 0.53 0.50
Austria 128 43.73 13.22 1.20 1.04 0.70 0.46 0.42 0.50 0.83 1.09 0.79 0.33 0.71 0.46
Croatia 104 45.08 11.92 0.74 0.97 0.44 0.50 0.23 0.42 0.11 0.18 0.78 0.31 0.65 0.48
France_I 96 45.81 10.51 1.09 1.22 0.81 0.39 0.20 0.40 2.04 1.43 0.30 0.28 0.26 0.44
France_II 28 44.96 9.71 1.08 1.22 0.81 0.40 0.64 0.49 1.01 0.86 0.23 0.27 0.41 0.50
Germany 153 43.55 11.49 1.20 1.23 0.51 0.50 0.47 0.50 1.09 2.51 0.52 0.28 0.94 0.24
Italy 130 47.90 14.76 0.69 1.38 0.29 0.45 0.15 0.36 0.85 6.30 0.70 0.35 0.93 0.25
Netherlands 160 50.95 12.33 0.88 1.19 0.15 0.35 0.60 0.49 1.11 1.48 0.64 0.34 0.00 0.00
Poland 169 39.51 10.48 1.26 1.21 0.30 0.46 0.13 0.33 0.19 0.27 0.79 0.29 0.93 0.25
Slovenia 114 29.24 11.08 0.87 1.11 0.37 0.48 0.28 0.45 0.27 0.29 0.65 0.32 0.97 0.16
Spain 130 53.43 13.28 0.62 0.85 0.30 0.46 0.14 0.35 0.39 0.62 0.80 0.30 0.77 0.42
Sweden 218 53.75 12.36 0.70 1.05 0.44 0.50 0.74 0.44 1.12 1.48 0.66 0.34 0.94 0.25






2 Population statistics and representativeness of samples

In this section, we compare the most recent official Eurostat data from 2016 with our sample data. Some of our samples are not meant to represent the whole country, as they were collected either on a lower regional level or focused on a specific agricultural system (cf. section 3 of this appendix).

We present national statistics for the variables farm size (utilized arable land and grassland), age, and gender of the farm holder. With respect to farm size, most of our samples contain farms larger than indicated in the Eurostat data. This is also true for the nationwide samples from Austria, Netherlands, Germany, and Sweden.

The respondents in most samples are younger than in the Eurostat data. The share of female farmers varies. In Sweden, Spain, Netherlands, Germany and France_II the samples are relative representative with respect to gender, the share of female farmers is larger in the samples from Austria, Poland, and Slovenia.

2.0.1 Representativeness for farm size (values in percent per size category)

Austria
Croatia
France
Germany
Italy
Netherlands
Poland
Slovenia
Spain
Sweden
FarmSize Eurostat Sample Eurostat Sample Eurostat France_I France_II Eurostat Sample Eurostat Sample Eurostat Sample Eurostat Sample Eurostat Sample Eurostat Sample Eurostat Sample
Zero ha 0.8 0.0 1.3 1.0 1.8 2.3 0.0 1.4 3.8 0.2 3.3 2.4 0.0 0.4 1.9 0.1 2.1 1.9 1.6 1.0 0.0
Less than 2 ha 10.3 0.0 37.8 16.3 10.6 0.0 3.7 3.9 1.5 34.0 12.2 7.8 0.7 21.2 8.3 24.9 10.3 25.3 2.4 1.0 0.0
From 2 to 4.9 ha 19.9 4.2 30.4 30.6 11.9 0.0 18.5 3.3 0.8 27.8 11.4 10.0 0.0 32.7 19.2 34.4 5.2 24.4 18.4 8.5 1.9
From 5 to 9.9 ha 16.6 8.4 14.9 26.5 9.2 2.3 0.0 16.1 4.6 15.7 12.2 13.1 1.4 21.7 17.9 23.0 21.6 14.9 19.2 24.9 10.8
From 10 to 19.9 ha 20.7 20.2 7.0 17.3 9.0 0.0 0.0 20.7 6.2 10.4 23.6 15.5 3.5 14.3 23.1 11.8 13.4 11.9 23.2 20.6 17.8
From 20 to 29.9 ha 11.4 15.1 2.4 3.1 6.0 1.1 7.4 9.7 11.5 4.1 14.6 11.3 5.7 4.3 14.7 3.1 18.6 5.3 5.6 9.0 6.6
From 30 to 49.9 ha 11.7 10.1 2.4 1.0 10.3 1.1 3.7 14.4 15.4 3.7 9.8 18.4 19.9 2.9 7.1 1.8 13.4 5.5 9.6 10.3 10.8
From 50 to 99.9 ha 6.4 18.5 2.6 2.0 19.4 11.4 18.5 17.4 28.5 2.6 4.9 16.8 35.5 1.6 5.1 0.7 12.4 5.3 8.8 11.9 16.9
100 ha or over 2.1 23.5 1.2 2.0 21.9 81.8 48.1 13.3 27.7 1.5 8.1 4.7 33.3 0.9 2.6 0.2 3.1 5.5 11.2 12.8 35.2
Total 100.0 100.0 100.0 99.8 100.0 100.0 99.9 100.0 100.0 100.0 100.1 100.0 100.0 100.0 99.9 100.0 100.1 100.0 100.0 100.0 100.0
a Eurostat database ef_m_farmang, using the most recent data from 2016.






2.0.2 Representativeness for age (values in percent per age category)

Austria
Croatia
France
Germany
Italy
Netherlands
Poland
Slovenia
Spain
Sweden
FarmSize Eurostat Sample Eurostat Sample Eurostat France_I France_II Eurostat Sample Eurostat Sample Eurostat Sample Eurostat Sample Eurostat Sample Eurostat Sample Eurostat Sample
Less than 25 years 1.8 10.4 0.7 3 0.7 2.2 0.0 0.6 6.1 0.4 3.9 0.4 2.7 0.7 9.0 0.5 50.0 0.2 4.7 0.4 0.0
From 25 to 34 years 10.5 17.4 4.4 20 7.6 13.5 11.1 6.8 21.1 3.6 21.9 3.7 11.3 9.5 33.7 4.1 28.7 3.6 7.9 4.9 5.6
From 35 to 39 years 10.1 20.9 5.4 19 7.3 20.2 29.6 7.2 15.6 3.9 8.6 4.6 8.0 10.1 16.9 4.5 6.5 4.8 2.4 4.8 10.3
From 40 to 44 years 12.3 10.4 7.1 10 10.0 15.7 18.5 10.0 12.9 6.0 14.1 9.4 8.7 13.0 12.7 7.7 6.5 8.6 4.7 7.0 12.6
From 45 to 54 years 35.0 16.5 21.8 25 29.9 27.0 22.2 35.8 27.9 21.1 17.2 34.2 30.0 28.3 17.5 25.9 1.9 26.0 37.0 22.6 26.2
From 55 to 64 years 22.0 16.5 27.8 20 29.3 20.2 18.5 31.3 15.0 24.0 23.4 29.0 28.0 26.7 10.2 28.8 6.5 25.4 22.8 27.6 26.6
65 years or over 7.4 7.8 32.7 3 15.1 1.1 0.0 8.2 1.4 40.9 10.9 18.7 11.3 11.7 0.0 28.5 0.0 31.2 20.5 32.7 18.7
Total 100.9 99.9 100.0 100 100.1 99.9 99.9 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.1 100.2 100.0 100.0 100.0
a Eurostat database ef_m_farmang, using the most recent data from 2016.






2.0.3 Representativeness for gender (values in percent)

Austria
Croatia
France
Germany
Italy
Netherlands
Poland
Slovenia
Spain
Sweden
FarmSize Eurostat Sample Eurostat Sample Eurostat France_I France_II Eurostat Sample Eurostat Sample Eurostat Sample Eurostat Sample Eurostat Sample Eurostat Sample Eurostat Sample
Females 31.3 45 26 16.5 21.3 9.9 22.2 9.6 12.5 31.5 17.1 5.2 7.2 29.4 60.9 20.2 48.2 22.6 22.5 15.5 18.4
Males 67.7 55 74 83.5 78.6 90.1 77.8 90.4 87.5 68.5 82.9 94.8 92.8 70.6 39.1 79.8 51.8 77.2 77.5 84.5 81.6
Total 100.9 100 100 100.0 100.1 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.2 100.0 100.0 100.0
a Eurostat database ef_m_farmang, using the most recent data from 2016.






3 Short narratives for each sample

3.1 Austria

In Austria, all arable farms who are part of the Integrated Administration and Control System data constituted the population for the survey. The survey region was Lower Austria with approximately 8,700 arable farms. The survey started at the end of September and ended in the beginning of December 2021. During farm advisory meetings for arable farmers the survey was explained, including a screening of the video translated into German. Each of the 194 farmers responded individually, out of which 128 farmers (66 percent) completed the lottery tasks and were used for analysis. All participants were compensated for their participation using vouchers consisting of a fixed payment of 10 Euros (in the form of a meal and a drink) and a payment linked to their choices. Sixty farmers provided an email for payments and the average payment was 11.87 Euro (ranging from 2.90 Euro to 65 Euro).

3.2 Croatia

In Croatia, the target group were winegrowers and wine producers from all over Croatia. A list of 637 winegrowers and wine producers was compiled, using publicly available data from web sources. Personalised emails with an invitation link to an online survey were sent to all 637 winegrowers or wine producers in the period from July to September 2021. A video explaining the experimental task was available in Croatian. A total of 130 respondents took part in the survey, of which 120 agreed to participate and 104 completed the survey in full. This results in an effective response rate of approximately 16 percent. 90 respondents (= 87 percent) provided an email address to be eligible for payment. Of all respondents, 70 (= 67 percent) signed up for the debriefing. One in ten participants received a voucher by email. The average value of the voucher was approximately 11 Euro (minimum 7 Euro, maximum 19 Euro).

3.3 France_I

In France, we had two sub-samples collected by two different teams. A video, explaining the experimental task, was available in French in both surveys. The main sub-sample (France I) consisted of potato farmers. They were invited to fill in an online survey through various channels: the link was posted repeatedly on the weekly newsletter of the national potato producer organization, it was also forwarded by emails from cooperatives to their potato-grower members, by the agricultural chamber of the department Pas de Calais, as well as by technical institutes at local and national levels. We do not know how many farmers were reached by the invitations, but we ended up with a final sample of 96 potato farmers. Sixty one farmers signed up for the debriefing. All participants were paid using vouchers. Seventy-nine farmers provided an email for payments and the average payment was 26.36 Euro (ranging from 8.70 Euro to 195 Euro).

3.4 France_II

A more limited data collection was organized in the North-West of France (France_II) to gather a convenience sample of organic farmers (vegetable growers, livestock and crops). The survey was promoted through the regional and departmental agricultural chambers of the region Pays de Loire and several networks of organic producers (e.g., GAB, CIVAM, Terre de liens, Bio Loire Océan). A total of 55 persons in close contact with organic farmers were contacted. Those who agreed to help circulate the survey, either forwarded an email by the researchers to organic farmers or promoted the survey in a newsletter. The survey was completed by 28 respondents (24 provided an email address to be eligible for payment and 19 signed up for the debriefing). Payments were made with vouchers to all participants. The average payment was 20 Euro (ranging from 13 Euro to 27 Euro).

3.5 Germany

In Germany, data were gathered with the help of an online panel provider specialising in farmer surveys. Using their own panel and another database, they reached out to 12,722 farmers out of which 727 decided to participate in the study. Filter questions at the panel provider’s survey tool screened out participants from other German-speaking countries or those not being involved in the decision of the farm. In total, 259 people passed the screening questions and opened the questionnaire, out of which 153 provided complete answers (= 59.1 percent of those who started). Participants had the opportunity to watch an instruction video. Payments were administered by the panel provider via bank transfer and ranged from 2.90 Euro to 65 Euro, averaging 8.83 Euro.

3.6 Italy

In Italy, olive growers from the Apulia region (Southern area of the country) have been targeted. Note that the regional average olive farm size is approximately one hectare. With the help of local farm advisors, potential respondents were contacted and recruited via email or phone calls. The final sample consists of 130 olive growers. Data were collected via face-to-face interviews during summer 2021. Filter questions ensured that only active farmers with a prominent role in the business decisions could take part in the survey. Each respondent received a cash payment at the end of the experiment and was informed at the beginning of the exchange rate regarding the lottery values (mean=10.02 Euro, Minimum= 2.90 Euro, Max=65 Euro).

3.7 Netherlands

In the Netherlands, the target population consisted of arable farmers. A market research company administered the online survey and sent it out to a random sample of 5,000 email addresses of arable farmers from their database in July and August 2021. A reminder was sent a week after the first invitation. Filter questions ensured that only arable farmers with substantial decision-making power and farm ownership could take part. A video, explaining the experimental task, was available in Dutch. The survey was completed by 160 participants (out of whom 102 signed up for and received the payment), implying an effective response rate of approximately 3 percent. 115 farmers signed up for the debriefing. All participants had the opportunity to receive a payment by bank transfer which was administered with the help of the market research company. The average payment was 16.09 Euro (SD = 17.21 Euro, Minimum = 4.35 Euro, Maximum = 97.50 Euro).

3.8 Poland

In Poland, 57 farmers were recruited by five agricultural advisors in three voivodeships: Podlaskie (30), Pomorskie (5) and Łódzkie (22). Farmers were invited to take part in an online survey during meetings with their advisors that took place between September 20 and October 31, 2021. An additional 112 farmers were selected from a panel of a market research company (Ariadna). The company ran a separate profile survey, in which 40 thousand panelists living in rural areas were asked to spontaneously state their employment sector (‘Agricultural’ out of 21 sectors defined by Central Statistics Office in Poland) and type of occupation/employment agreement (farmers). Around 7,000 respondents who qualified were contacted with the link to the study on September 23, 2021. At the beginning of the survey, they were asked to confirm their previous responses (double spontaneous screening on employment sectors and occupations). 386 panelists opened the link, and 112 remained in the final sample. We asked about contact details. We informed participants that payments could only be administered after they sign a special form and send it back by scan or post to the University of Warsaw. On October 22, 2021, by individual emails/post (envelope with a return stamp), we requested such documents. The document contained a signature, name, surname and account number. Direct bank transfers were made by the University of Warsaw financial section to 94 farmers who had sent the necessary documents, using a rate of 0.05 PLN (approximately 0.01 EURO) per experimental currency unit. The average lottery result for all 169 participants was 39.70 PLN. The average of 94 payments transferred was 43 PLN (9.34 EUR); it ranged between 19.50 PLN (4.24 EU) and 90 PLN (19.56 PLN).

3.9 Slovenia

In Slovenia, the target population were young farmers and young family members who actively engage in farming and are likely to take over their family farm in the upcoming years. Potential respondents were recruited via email and on farm and other events, which were organised or attended by the members of the Association of Slovenian Rural Youth between July and October 2021. The Association has about 3,000 members and the final sample consisted of 114 respondents. 88 respondents were interviewed face-to-face, whereas 26 respondents filled the survey on-line and thus had access to a video explaining the experimental task in Slovenian. The opportunity to receive a voucher for different products and services of the Association was offered to all participants, to which 93 responded by providing their email. The average payment was 9.15 Euro (ranging from 2.90 Euro to 45 Euro).

3.10 Spain

In Spain, the target population consisted of the members of two olive oil cooperatives in Andalusia. The cooperatives have 1,482 members and 132 of them responded to an invitation to an in-person meeting at the cooperative’s premises (response rate 8.9%). During the meetings, instructions for the survey were explained following the structure of the questionnaire, including a screening of the video translated to Spanish. Each farmer responded individually to the survey on their mobile device, having access to all the instructions individually. All participants were compensated for their participation with a fixed payment of 10 Euros and a payment linked to their choices. The average total payment (including the show-up fee) was 15.70 euros (ranging from 5.80 to 36 Euro) with an average variable payment being 5.70 (from -4.20 Euro to 26 Euro). Participants could exchange their payment for olive oil at the cooperative’s shop. 69% farmers signed up for the de-briefing.

3.11 Sweden

In Sweden, all registered farming businesses with an email address were part of the target population based on a list obtained from the Statistical Bureau of Sweden. 36,940 businesses met this criterion which is more than half of all registered farming businesses. Personalized invitation links to an online survey (programmed in Qualtrics) were sent to a simple random sample of 19,000 registered farm businesses with an email address in November and December 2021. Approximately five percent of the email addresses were invalid. The survey was completed by 218 respondents (209 or 96 percent of whom provided an email address to be eligible for payment), implying an effective response rate of approximately one percent. Out of all respondents, 188 (= 86 percent) signed up for the debriefing. One in ten participants received a payment by bank transfer which was administered with the help of a market research company. In total, 24 respondents were randomly selected for payment. The average payment was 1,365 SEK (132 Euro), ranging from 680 SEK (66 Euro) to 2,080 SEK (202 Euro).






4 Structural models with covariates

The following tables present coefficient estimates for the structural models from Tables 4 (EUT), 5 (EUT expo power), 6 (CPT) in the main text, but here the models include covariates (the seven common covariates discussed in the main text). To allow for an easy interpretation of the structural model parameters, all variables have been mean-centered (i.e., we use deviation from the sample mean).

Note that there are fewer observations due to list-wise missing data for some of the covariates (recall that participants could choose not to respond to some of the demographic questions). Please also note that in some instances, models did not converge or that models may have converged at local maxima (e.g., Spain in the EUT model). This is because, many of the covariates are dummy variables (little variation in the independent variables) and there is limited variation in the dependent variable (respondents tend to cluster on some rows for their switch, see section 1 of this appendix). Taken together, in a small sample, this can lead to flat areas of the likelihood function which increases the risk of reaching local maxima or non-converging models. One could solve this problem for instance by dropping observations, co-variates, or changing starting values, but given the magnitude of this project, we have refrained from doing so.






4.1 Results over all samples in Expected Utility model with covariates (re-estimation of table 4 in main text)

  All Countries BJR2014 Austria Croatia France_I France_II Germany Italy Netherlands Poland Slovenia Spain Sweden
r 0.211 0.225 0.223 0.225 0.176 0.161 0.225 0.193 0.235 0.202 0.110 -3.157 0.233
  [ 0.201; 0.220] [ 0.196; 0.254] [ 0.173; 0.272] [ 0.192; 0.259] [ 0.114; 0.238] [ 0.077; 0.244] [ 0.200; 0.251] [ 0.144; 0.243] [ 0.208; 0.261] [ 0.170; 0.235] [-0.016; 0.236] [-3.925; -2.389] [ 0.214; 0.252]
Age -0.000 -0.001 -0.002 -0.001 0.003 0.006 0.001 -0.003 -0.002 -0.002 -0.003 0.033 -0.000
  [-0.001; 0.000] [-0.004; 0.003] [-0.006; 0.002] [-0.004; 0.002] [-0.001; 0.007] [-0.003; 0.015] [-0.002; 0.004] [-0.005; -0.000] [-0.004; 0.000] [-0.005; 0.001] [-0.010; 0.004] [ 0.012; 0.054] [-0.002; 0.002]
NbChildren 0.000 0.022 0.009 -0.015 0.011 0.025 0.006 -0.010 -0.001 -0.015 0.067 -4.273 -0.005
  [-0.007; 0.007] [ 0.001; 0.044] [-0.028; 0.046] [-0.051; 0.020] [-0.025; 0.048] [-0.099; 0.149] [-0.015; 0.027] [-0.024; 0.005] [-0.019; 0.017] [-0.043; 0.013] [ 0.014; 0.119] [-4.788; -3.758] [-0.028; 0.018]
Trust 0.013 0.011 -0.039 -0.038 0.059 0.124 0.000 -0.103 0.010 -0.070 -0.078 0.220 -0.002
  [-0.007; 0.033] [-0.048; 0.070] [-0.128; 0.050] [-0.156; 0.079] [-0.028; 0.146] [-0.353; 0.601] [-0.054; 0.054] [-0.369; 0.163] [-0.044; 0.063] [-0.191; 0.051] [-0.180; 0.024] [ 0.097; 0.342] [-0.043; 0.040]
FarmSize -0.003 -0.015 0.024 0.040 0.010 0.079 -0.006 -0.006 0.009 0.024 0.274 0.002 -0.012
  [-0.007; 0.001] [-0.044; 0.015] [-0.007; 0.055] [-0.293; 0.373] [-0.026; 0.046] [-0.016; 0.173] [-0.019; 0.008] [-0.012; -0.000] [-0.014; 0.031] [-0.064; 0.111] [ 0.057; 0.490] [-0.011; 0.016] [-0.027; 0.003]
LandOwned -0.003 0.002 0.127 -0.049 -0.191 -0.115 0.003 0.052 -0.042 0.010 0.538 0.297 -0.010
  [-0.032; 0.026] [-0.168; 0.172] [-0.081; 0.334] [-0.123; 0.024] [-0.460; 0.078] [-0.591; 0.362] [-0.090; 0.096] [-0.041; 0.146] [-0.117; 0.033] [-0.066; 0.086] [ 0.111; 0.965] [-0.167; 0.760] [-0.065; 0.044]
LL (NULL) -26360.861 -2397.471 -2125.360 -2035.295 -1830.972 -524.104 -2433.254 -2290.275 -2794.475 -3339.103 -1873.580 -2665.092 -4373.276
LL (Converged) -25480.986 -2284.943 -2061.449 -1912.541 -1791.846 -499.521 -2312.386 -2237.132 -2675.186 -3198.712 -1790.345 -2665.608 -4105.265
Num. obs. 229878 21186 19008 17622 16038 4554 21186 20196 24750 28908 16236 23364 38016
Num. resp. 1161 107 96 89 81 23 107 102 125 146 82 118 192
BIC 51036.043 4629.652 4182.014 3883.744 3641.789 1049.585 4684.539 4533.744 5411.071 6459.055 3638.860 5391.570 8273.805
AIC 50973.971 4581.885 4134.898 3837.083 3595.692 1011.043 4636.772 4486.264 5362.372 6409.424 3592.691 5343.216 8222.530
AICc 50973.972 4581.889 4134.902 3837.087 3595.697 1011.061 4636.776 4486.269 5362.375 6409.427 3592.696 5343.219 8222.532
Pseudo R2 0.033 0.047 0.030 0.060 0.021 0.047 0.050 0.023 0.043 0.042 0.044 -0.000 0.061






4.2 Results over all samples in Exponential Power model with covariates (re-estimation of table 5 in main text)

  All Countries BJR2014 Austria Croatia France_I France_II Germany Italy Netherlands Slovenia Spain Sweden
alpha 0.212 0.291 0.143 0.249 0.174 0.200 0.214 0.244 0.200 0.200 0.136 0.198
  [ 0.201; 0.223] [ 0.261; 0.321] [ 0.069; 0.218] [ 0.214; 0.283] [ 0.076; 0.273] [ 0.113; 0.287] [ 0.176; 0.251] [ 0.216; 0.272] [ 0.153; 0.246] [ 0.112; 0.288] [-0.061; 0.333] [ 0.164; 0.232]
alpha_Age -0.000 -0.001 -0.001 -0.002 0.003 0.000 -0.000 -0.001 -0.002 0.000 0.005 0.001
  [-0.001; 0.001] [-0.004; 0.002] [-0.003; 0.002] [-0.005; 0.000] [-0.001; 0.008] [-0.013; 0.013] [-0.003; 0.003] [-0.004; 0.002] [-0.007; 0.003] [-0.007; 0.007] [-0.003; 0.014] [-0.001; 0.003]
alpha_NbChildren 0.005 0.010 -0.007 -0.021 -0.010 0.000 -0.007 0.012 -0.014 0.000 0.013 -0.000
  [-0.007; 0.017] [-0.013; 0.033] [-0.020; 0.006] [-0.054; 0.012] [-0.035; 0.015] [-0.119; 0.119] [-0.029; 0.014] [-0.070; 0.095] [-0.066; 0.038] [-0.041; 0.041] [-0.195; 0.222] [-0.025; 0.024]
alpha_Trust -0.016 0.005 0.010 -0.070 -0.011 0.000 -0.022 -0.020 0.011 0.000 0.102 -0.054
  [-0.041; 0.008] [-0.051; 0.061] [-0.071; 0.090] [-0.155; 0.014] [-0.100; 0.077] [-0.225; 0.225] [-0.092; 0.047] [-0.108; 0.069] [-0.081; 0.103] [-0.202; 0.202] [-0.200; 0.403] [-0.096; -0.012]
alpha_FarmSize -0.021 -0.029 0.066 -0.011 -0.000 0.000 -0.011 -0.003 -0.001 0.000 -0.040 -0.043
  [-0.033; -0.009] [-0.066; 0.009] [ 0.038; 0.094] [-0.144; 0.123] [-0.031; 0.030] [-0.141; 0.141] [-0.015; -0.008] [-0.008; 0.001] [-0.046; 0.043] [-0.134; 0.134] [-0.494; 0.413] [-0.088; 0.003]
alpha_LandOwned -0.013 -0.040 0.415 -0.024 0.101 0.000 0.106 0.022 -0.054 0.000 0.055 -0.040
  [-0.041; 0.016] [-0.187; 0.106] [ 0.166; 0.664] [-0.125; 0.077] [-0.214; 0.415] [-0.390; 0.390] [-0.027; 0.238] [-0.069; 0.112] [-0.213; 0.105] [-0.374; 0.374] [-0.477; 0.586] [-0.102; 0.022]
beta -0.021 0.115 -0.382 0.065 -0.129 0.200 -0.104 0.084 -0.158 0.200 0.413 -0.186
  [-0.057; 0.016] [ 0.076; 0.153] [-0.768; 0.005] [-0.019; 0.149] [-0.615; 0.356] [-0.034; 0.434] [-0.264; 0.055] [ 0.024; 0.144] [-0.385; 0.069] [-0.021; 0.421] [-0.752; 1.578] [-0.358; -0.013]
beta_Age 0.000 0.000 -0.002 0.000 0.007 0.000 -0.003 0.001 0.000 0.000 -0.021 0.001
  [-0.002; 0.002] [-0.004; 0.004] [-0.010; 0.005] [-0.005; 0.005] [-0.021; 0.035] [-0.027; 0.027] [-0.009; 0.003] [-0.004; 0.007] [-0.016; 0.016] [-0.018; 0.018] [-0.081; 0.038] [-0.005; 0.007]
beta_NbChildren 0.007 -0.028 0.013 0.011 -0.092 0.000 -0.060 0.012 -0.063 0.000 -0.236 -0.022
  [-0.013; 0.026] [-0.051; -0.005] [-0.043; 0.070] [-0.058; 0.080] [-0.259; 0.075] [-0.284; 0.284] [-0.151; 0.032] [-0.043; 0.068] [-0.270; 0.143] [-0.092; 0.092] [-0.533; 0.061] [-0.081; 0.037]
beta_Trust -0.094 -0.011 0.202 -0.038 -0.278 0.000 -0.032 0.033 -0.012 0.000 -0.153 -0.178
  [-0.167; -0.020] [-0.073; 0.051] [-0.046; 0.449] [-0.237; 0.160] [-0.705; 0.149] [-0.561; 0.561] [-0.225; 0.161] [-0.177; 0.243] [-0.358; 0.334] [-0.491; 0.491] [-0.479; 0.172] [-0.306; -0.050]
beta_FarmSize -0.106 0.014 0.117 -0.281 -0.052 0.000 -0.109 0.028 -0.041 0.000 -0.096 -0.174
  [-0.162; -0.051] [-0.029; 0.058] [-0.018; 0.252] [-0.777; 0.214] [-0.138; 0.033] [-0.377; 0.377] [-0.221; 0.003] [-0.001; 0.056] [-0.270; 0.188] [-0.294; 0.294] [-1.616; 1.425] [-0.368; 0.020]
beta_LandOwned -0.040 -0.036 1.538 0.063 0.643 0.000 0.178 -0.071 -0.142 0.000 -0.171 -0.178
  [-0.112; 0.032] [-0.246; 0.174] [ 0.347; 2.729] [-0.046; 0.171] [ 0.003; 1.283] [-0.877; 0.877] [-0.251; 0.606] [-0.258; 0.116] [-0.701; 0.417] [-0.712; 0.712] [-1.074; 0.731] [-0.368; 0.013]
LL (NULL) -26360.861 -2397.471 -2125.360 -2035.295 -1830.972 -524.104 -2433.254 -2290.275 -2794.475 -1873.580 -2665.092 -4373.276
LL (Converged) -25403.689 -2205.430 -2020.445 -1892.599 -1772.473 -518.717 -2296.813 -2244.835 -2650.197 -1820.267 -2638.995 -4068.645
Num. obs. 459756 42372 38016 35244 32076 9108 42372 40392 49500 32472 46728 76032
Num. resp. 1161 107 96 89 81 23 107 102 125 82 118 192
BIC 50963.840 4538.711 4167.439 3910.840 3669.457 1146.836 4721.476 4616.946 5430.112 3765.191 5407.016 8272.157
AIC 50831.379 4434.860 4064.889 3809.199 3568.946 1061.433 4617.625 4513.670 5324.395 3664.534 5301.991 8161.290
AICc 50831.379 4434.868 4064.898 3809.208 3568.956 1061.468 4617.632 4513.677 5324.401 3664.543 5301.998 8161.294
Pseudo R2 0.036 0.080 0.049 0.070 0.032 0.010 0.056 0.020 0.052 0.028 0.010 0.070






4.3 Results over all samples in Prospect Theory model with covariates (re-estimation of table 6 in main text)

  All Countries BJR2014 Austria Croatia France_I Italy Netherlands Poland Slovenia Spain Sweden
sigma 0.311 0.296 0.316 0.339 0.292 0.303 0.316 0.290 0.316 0.257 0.329
  [ 0.306; 0.316] [ 0.276; 0.316] [ 0.298; 0.334] [ 0.325; 0.353] [ 0.271; 0.313] [ 0.277; 0.328] [ 0.301; 0.331] [ 0.273; 0.306] [ 0.299; 0.333] [ 0.229; 0.285] [ 0.318; 0.340]
sigma_Age -0.001 -0.004 -0.001 -0.001 0.000 -0.002 -0.002 -0.002 -0.001 0.004 -0.001
  [-0.001; -0.000] [-0.006; -0.001] [-0.002; 0.001] [-0.003; -0.000] [-0.001; 0.002] [-0.003; -0.000] [-0.003; -0.000] [-0.004; -0.001] [-0.003; 0.001] [ 0.001; 0.006] [-0.002; -0.000]
sigma_NbChildren -0.005 0.015 -0.001 -0.002 -0.011 -0.005 -0.019 -0.003 -0.009 0.041 -0.002
  [-0.009; -0.001] [-0.000; 0.031] [-0.022; 0.019] [-0.020; 0.015] [-0.026; 0.004] [-0.015; 0.004] [-0.034; -0.004] [-0.016; 0.010] [-0.024; 0.007] [ 0.004; 0.078] [-0.013; 0.008]
sigma_Trust 0.018 -0.007 -0.010 0.021 0.049 -0.011 0.007 -0.063 -0.007 0.052 -0.009
  [ 0.008; 0.028] [-0.047; 0.034] [-0.054; 0.034] [-0.008; 0.051] [ 0.006; 0.091] [-0.072; 0.051] [-0.025; 0.039] [-0.140; 0.014] [-0.043; 0.029] [-0.008; 0.112] [-0.032; 0.014]
sigma_FarmSize -0.008 -0.008 0.012 -0.087 0.001 -0.012 0.014 -0.062 0.139 -0.013 -0.016
  [-0.013; -0.004] [-0.025; 0.009] [-0.005; 0.030] [-0.214; 0.041] [-0.013; 0.015] [-0.039; 0.016] [-0.012; 0.040] [-0.118; -0.006] [ 0.089; 0.190] [-0.051; 0.024] [-0.025; -0.007]
sigma_LandOwned -0.003 0.011 0.092 -0.056 -0.032 -0.003 0.005 -0.045 0.110 0.056 -0.023
  [-0.017; 0.011] [-0.094; 0.115] [ 0.026; 0.157] [-0.100; -0.012] [-0.107; 0.043] [-0.045; 0.039] [-0.044; 0.054] [-0.084; -0.006] [ 0.019; 0.202] [-0.036; 0.148] [-0.055; 0.008]
lambda 1.592 2.278 1.530 1.829 1.763 1.217 1.240 1.828 2.038 2.531 1.297
  [ 1.518; 1.667] [ 1.927; 2.630] [ 1.263; 1.797] [ 1.612; 2.047] [ 1.392; 2.134] [ 0.612; 1.821] [ 1.019; 1.462] [ 1.547; 2.109] [ 1.733; 2.342] [ 2.025; 3.038] [ 1.140; 1.453]
lambda_Age -0.002 0.020 0.003 -0.005 0.016 -0.000 0.006 -0.009 0.029 -0.046 -0.008
  [-0.008; 0.003] [-0.019; 0.058] [-0.015; 0.020] [-0.021; 0.011] [-0.017; 0.050] [-0.019; 0.019] [-0.012; 0.025] [-0.035; 0.017] [-0.003; 0.062] [-0.092; 0.001] [-0.022; 0.006]
lambda_NbChildren -0.020 -0.307 -0.019 -0.006 0.113 0.159 -0.082 0.115 -0.318 -0.551 -0.121
  [-0.088; 0.048] [-0.555; -0.059] [-0.236; 0.199] [-0.225; 0.212] [-0.182; 0.408] [-0.089; 0.408] [-0.295; 0.130] [-0.085; 0.314] [-0.573; -0.064] [-1.100; -0.003] [-0.285; 0.044]
lambda_Trust -0.252 0.112 0.015 -0.283 -0.314 0.129 -0.128 0.042 0.763 -0.410 -0.400
  [-0.399; -0.106] [-0.564; 0.788] [-0.457; 0.487] [-0.671; 0.105] [-0.977; 0.348] [-0.716; 0.973] [-0.563; 0.307] [-1.260; 1.343] [ 0.067; 1.458] [-1.300; 0.480] [-0.730; -0.069]
lambda_FarmSize -0.201 -0.075 -0.280 -1.889 -0.134 -0.375 -0.224 -0.248 -0.520 -0.247 -0.134
  [-0.286; -0.115] [-0.366; 0.217] [-0.449; -0.111] [-3.701; -0.078] [-0.389; 0.120] [-1.122; 0.372] [-0.439; -0.010] [-1.554; 1.057] [-1.148; 0.107] [-0.791; 0.297] [-0.306; 0.039]
lambda_LandOwned 0.010 -1.671 0.064 0.363 1.920 -0.488 0.045 -0.421 -0.026 0.114 -0.342
  [-0.203; 0.223] [-3.204; -0.138] [-1.066; 1.194] [-0.166; 0.892] [ 0.427; 3.413] [-1.183; 0.208] [-0.564; 0.655] [-1.178; 0.335] [-1.403; 1.350] [-1.422; 1.650] [-0.791; 0.107]
gamma 0.572 0.699 0.660 0.589 0.564 0.542 0.638 0.612 0.556 0.417 0.550
  [ 0.549; 0.595] [ 0.577; 0.820] [ 0.574; 0.747] [ 0.516; 0.663] [ 0.457; 0.672] [ 0.432; 0.652] [ 0.570; 0.706] [ 0.526; 0.698] [ 0.463; 0.650] [ 0.297; 0.537] [ 0.499; 0.602]
gamma_Age -0.000 0.005 -0.005 0.001 0.009 -0.004 -0.000 -0.002 -0.002 0.006 0.002
  [-0.002; 0.002] [-0.007; 0.017] [-0.011; 0.000] [-0.005; 0.006] [ 0.000; 0.019] [-0.008; 0.000] [-0.006; 0.005] [-0.011; 0.007] [-0.009; 0.004] [-0.006; 0.018] [-0.002; 0.006]
gamma_NbChildren 0.011 -0.011 0.019 -0.035 0.059 -0.023 0.058 -0.053 0.118 0.026 -0.013
  [-0.011; 0.032] [-0.072; 0.051] [-0.056; 0.094] [-0.093; 0.024] [-0.035; 0.153] [-0.079; 0.034] [-0.007; 0.122] [-0.118; 0.012] [ 0.046; 0.190] [-0.084; 0.136] [-0.066; 0.039]
gamma_Trust -0.021 0.134 -0.171 -0.111 0.060 -0.043 -0.006 -0.109 -0.054 0.097 -0.009
  [-0.066; 0.024] [-0.085; 0.353] [-0.305; -0.037] [-0.261; 0.040] [-0.133; 0.252] [-0.166; 0.080] [-0.137; 0.124] [-0.363; 0.144] [-0.238; 0.131] [-0.080; 0.274] [-0.117; 0.100]
gamma_FarmSize -0.011 -0.026 0.060 0.027 0.004 -0.026 -0.045 0.300 0.003 0.011 -0.032
  [-0.040; 0.018] [-0.106; 0.054] [-0.010; 0.129] [-0.882; 0.937] [-0.101; 0.109] [-0.143; 0.090] [-0.103; 0.012] [-0.092; 0.691] [-0.167; 0.174] [-0.078; 0.099] [-0.085; 0.021]
gamma_LandOwned 0.027 -0.209 0.049 0.020 -0.357 0.211 -0.100 0.103 0.339 0.163 -0.012
  [-0.038; 0.092] [-0.674; 0.257] [-0.345; 0.442] [-0.134; 0.173] [-0.845; 0.132] [ 0.031; 0.392] [-0.293; 0.093] [-0.100; 0.306] [-0.109; 0.786] [-0.274; 0.600] [-0.140; 0.116]
LL (NULL) -26360.861 -2397.471 -2125.360 -2035.295 -1830.972 -2290.275 -2794.475 -3339.103 -1873.580 -2665.092 -4373.276
LL (Converged) -23877.820 -2106.243 -1962.735 -1684.392 -1701.652 -2098.064 -2529.287 -3001.043 -1608.398 -2527.611 -3696.122
Num. obs. 689634 63558 57024 52866 48114 60588 74250 86724 48708 70092 114048
Num. resp. 1161 107 96 89 81 102 125 146 82 118 192
BIC 47997.630 4411.561 4122.592 3564.543 3597.368 4394.341 5260.448 6206.755 3411.080 5256.059 7601.843
AIC 47791.640 4248.486 3961.470 3404.784 3439.304 4232.128 5094.575 6038.087 3252.796 5091.223 7428.244
AICc 47791.641 4248.497 3961.482 3404.797 3439.318 4232.139 5094.584 6038.095 3252.810 5091.232 7428.250
Pseudo R2 0.094 0.121 0.077 0.172 0.071 0.084 0.095 0.101 0.142 0.052 0.155






5 Mid-point approach

The mid-point approach is based on approximations of parameter values for lottery choices per individual. Each combination of lottery choices under monotonous switching is consistent with certain intervals for the three CPT parameters. Mid-points of these intervals are used to approximate the three parameters per individual. In the main text, the distribution of these approximations is displayed in figure 1. Here, we provide additional statistics for the pooled data and per sample (Summary statistics for mid-point approximations). Finally, we also provide higher resolution figures for the distribution of the three parameters per sample (‘Plots’).






5.1 Summary statistics for mid-point approximations

The summary statistics for all countries exclude the sample from BJR2014.

5.1.1 Mid-point approach summary statistics per sample

Basic descriptives
grouped by BJR2014
var n mean md sd range
σ 107 0.89 0.59 0.67 1.88 (0.08-1.95)
λ 107 3.16 2.10 3.20 11.55 (0.08-11.62)
γ 107 0.63 0.58 0.45 1.85 (0.05-1.9)

 

Basic descriptives
grouped by All Countries
var n mean md sd range
σ 1424 0.65 0.52 0.51 1.88 (0.08-1.95)
λ 1424 3.51 1.98 3.66 11.55 (0.08-11.62)
γ 1424 0.65 0.58 0.41 1.85 (0.05-1.9)

 

Basic descriptives
grouped by Austria
var n mean md sd range
σ 128 0.57 0.58 0.39 1.88 (0.08-1.95)
λ 128 3.13 1.60 3.41 11.03 (0.08-11.1)
γ 128 0.61 0.58 0.37 1.85 (0.05-1.9)

 

Basic descriptives
grouped by Croatia
var n mean md sd range
σ 104 0.71 0.61 0.49 1.88 (0.08-1.95)
λ 104 3.40 2.02 3.23 11.55 (0.08-11.62)
γ 104 0.68 0.62 0.40 1.85 (0.05-1.9)

 

Basic descriptives
grouped by France_I
var n mean md sd range
σ 96 0.60 0.49 0.51 1.88 (0.08-1.95)
λ 96 3.40 1.89 3.81 11.55 (0.08-11.62)
γ 96 0.64 0.58 0.43 1.85 (0.05-1.9)

 

Basic descriptives
grouped by France_II
var n mean md sd range
σ 28 0.62 0.46 0.53 1.88 (0.08-1.95)
λ 28 2.79 1.40 3.63 11 (0.1-11.1)
γ 28 0.55 0.56 0.42 1.85 (0.05-1.9)

 

Basic descriptives
grouped by Germany
var n mean md sd range
σ 153 0.72 0.59 0.52 1.88 (0.08-1.95)
λ 153 3.17 1.98 3.37 11.55 (0.08-11.62)
γ 153 0.68 0.58 0.44 1.85 (0.05-1.9)

 

Basic descriptives
grouped by Italy
var n mean md sd range
σ 130 0.62 0.54 0.49 1.88 (0.08-1.95)
λ 130 4.34 2.09 4.13 11.53 (0.1-11.62)
γ 130 0.62 0.58 0.35 1.85 (0.05-1.9)

 

Basic descriptives
grouped by Netherlands
var n mean md sd range
σ 154 0.65 0.49 0.54 1.88 (0.08-1.95)
λ 154 3.09 1.54 3.66 11.55 (0.08-11.62)
γ 154 0.63 0.58 0.41 1.85 (0.05-1.9)

 

Basic descriptives
grouped by Poland
var n mean md sd range
σ 169 0.72 0.58 0.55 1.88 (0.08-1.95)
λ 169 3.88 2.35 3.92 11.55 (0.08-11.62)
γ 169 0.61 0.56 0.40 1.85 (0.05-1.9)

 

Basic descriptives
grouped by Slovenia
var n mean md sd range
σ 114 0.64 0.52 0.46 1.88 (0.08-1.95)
λ 114 3.66 2.08 3.77 11.55 (0.08-11.62)
γ 114 0.75 0.66 0.42 1.85 (0.05-1.9)

 

Basic descriptives
grouped by Spain
var n mean md sd range
σ 130 0.60 0.49 0.54 1.88 (0.08-1.95)
λ 130 3.66 2.97 3.34 11.03 (0.08-11.1)
γ 130 0.66 0.58 0.37 1.85 (0.05-1.9)

 

Basic descriptives
grouped by Sweden
var n mean md sd range
σ 218 0.66 0.49 0.54 1.88 (0.08-1.95)
λ 218 3.54 1.98 3.69 11.55 (0.08-11.62)
γ 218 0.68 0.58 0.44 1.85 (0.05-1.9)






5.2 Plots

The plots are similar to those from the main text but in a larger resolution.

5.3 Regression analysis

In this part, we present regression results to explain the heterogeneity in individual CPT parameters estimated with the mid-point approach. For each parameter (\(\sigma\), \(\lambda\), \(\gamma\)), an OLS regression is presented that estimates the effect of covariates on the size of these parameters.

5.3.1 Parameter estimatess for CPT Model derived from mid-point approach (\(\sigma\))

  All Countries BJR2014 Austria Croatia France_I France_II Germany Italy Netherlands Poland Slovenia Spain Sweden
Constant 0.640 0.891 0.486 0.737 0.610 0.558 0.711 0.657 0.612 0.717 0.667 0.580 0.642
  [ 0.611; 0.669] [ 0.765; 1.017] [ 0.420; 0.552] [ 0.634; 0.841] [ 0.493; 0.728] [ 0.344; 0.772] [ 0.610; 0.812] [ 0.569; 0.746] [ 0.515; 0.709] [ 0.627; 0.808] [ 0.563; 0.772] [ 0.482; 0.678] [ 0.569; 0.714]
Age 0.001 0.011 0.003 0.002 -0.003 0.001 0.001 0.006 0.002 -0.003 0.010 0.002 -0.002
  [-0.002; 0.003] [-0.005; 0.026] [-0.002; 0.009] [-0.007; 0.011] [-0.015; 0.009] [-0.025; 0.027] [-0.009; 0.010] [-0.001; 0.013] [-0.008; 0.011] [-0.012; 0.007] [-0.001; 0.020] [-0.007; 0.011] [-0.009; 0.005]
NbChildren 0.003 0.022 -0.024 0.035 -0.027 -0.188 -0.016 0.103 -0.018 -0.002 -0.076 -0.005 -0.007
  [-0.023; 0.030] [-0.092; 0.136] [-0.092; 0.044] [-0.079; 0.149] [-0.127; 0.074] [-0.378; 0.001] [-0.102; 0.070] [ 0.039; 0.166] [-0.107; 0.071] [-0.080; 0.076] [-0.169; 0.017] [-0.139; 0.130] [-0.093; 0.078]
Trust -0.019 -0.096 0.025 -0.123 -0.046 -0.181 0.123 -0.126 0.100 -0.183 -0.094 0.107 -0.022
  [-0.081; 0.043] [-0.392; 0.201] [-0.116; 0.166] [-0.361; 0.115] [-0.340; 0.247] [-0.666; 0.305] [-0.081; 0.328] [-0.386; 0.134] [-0.100; 0.301] [-0.455; 0.088] [-0.334; 0.145] [-0.184; 0.398] [-0.189; 0.145]
FarmSize -0.009 0.009 -0.053 0.455 -0.018 -0.107 -0.021 -0.004 0.061 -0.163 0.093 -0.072 0.034
  [-0.021; 0.003] [-0.146; 0.165] [-0.114; 0.008] [-0.116; 1.025] [-0.109; 0.074] [-0.383; 0.169] [-0.059; 0.018] [-0.018; 0.009] [-0.045; 0.166] [-0.490; 0.165] [-0.270; 0.455] [-0.255; 0.111] [-0.021; 0.090]
LandOwned -0.100 -0.033 -0.156 -0.025 0.142 0.401 0.162 -0.336 -0.043 -0.206 -0.181 -0.238 -0.107
  [-0.187; -0.012] [-0.693; 0.628] [-0.357; 0.044] [-0.369; 0.319] [-0.303; 0.586] [-0.653; 1.455] [-0.232; 0.555] [-0.615; -0.058] [-0.324; 0.238] [-0.544; 0.133] [-0.569; 0.206] [-0.598; 0.122] [-0.323; 0.109]
IndivOwner 0.062 0.264 -0.003 0.033 -0.228 -0.244 0.125 0.486   -0.351 0.084 0.130 0.302
  [-0.005; 0.129] [-0.052; 0.580] [-0.160; 0.155] [-0.187; 0.253] [-0.522; 0.067] [-0.712; 0.225] [-0.284; 0.534] [ 0.108; 0.864]   [-0.897; 0.196] [-0.500; 0.667] [-0.145; 0.405] [-0.016; 0.621]
R2 0.008 0.064 0.073 0.046 0.041 0.262 0.044 0.194 0.023 0.055 0.084 0.035 0.033
Adj. R2 0.003 0.008 0.011 -0.025 -0.037 -0.014 -0.013 0.142 -0.019 0.014 0.011 -0.018 0.002
Num. obs. 1156 107 96 88 81 23 107 100 124 145 82 118 192






5.3.2 Parameter estimatess for CPT Model derived from mid-point approach (\(\lambda\))

  All Countries BJR2014 Austria Croatia France_I France_II Germany Italy Netherlands Poland Slovenia Spain Sweden
Constant 3.535 3.156 3.298 3.262 3.340 3.104 3.226 4.035 3.151 3.918 3.430 3.776 3.718
  [ 3.323; 3.748] [ 2.552; 3.760] [ 2.599; 3.997] [ 2.604; 3.921] [ 2.534; 4.145] [ 1.498; 4.710] [ 2.556; 3.895] [ 3.251; 4.819] [ 2.496; 3.807] [ 3.264; 4.572] [ 2.615; 4.246] [ 3.167; 4.386] [ 3.184; 4.252]
Age 0.019 0.017 -0.053 -0.022 0.074 0.113 0.037 0.027 0.055 0.085 -0.038 -0.025 0.016
  [ 0.002; 0.036] [-0.057; 0.092] [-0.110; 0.004] [-0.079; 0.035] [-0.009; 0.156] [-0.084; 0.309] [-0.025; 0.100] [-0.032; 0.087] [-0.007; 0.118] [ 0.017; 0.154] [-0.119; 0.042] [-0.080; 0.031] [-0.036; 0.068]
NbChildren 0.142 0.389 0.650 0.089 0.264 0.172 0.537 -0.223 0.077 -0.033 0.558 -0.291 0.328
  [-0.051; 0.335] [-0.157; 0.934] [-0.067; 1.367] [-0.634; 0.812] [-0.427; 0.954] [-1.251; 1.596] [-0.034; 1.107] [-0.783; 0.338] [-0.524; 0.679] [-0.596; 0.529] [-0.167; 1.283] [-1.127; 0.545] [-0.299; 0.954]
Trust -0.318 -0.448 -0.386 0.920 -1.596 1.859 -0.910 0.099 -1.086 1.016 0.610 -0.585 -0.733
  [-0.766; 0.131] [-1.869; 0.973] [-1.868; 1.096] [-0.593; 2.433] [-3.608; 0.415] [-1.786; 5.505] [-2.267; 0.448] [-2.204; 2.401] [-2.444; 0.272] [-0.942; 2.974] [-1.256; 2.475] [-2.389; 1.219] [-1.961; 0.495]
FarmSize 0.005 0.279 0.584 0.220 0.174 1.808 0.024 -0.017 -0.160 -0.188 -0.050 1.299 -0.188
  [-0.084; 0.093] [-0.467; 1.025] [-0.055; 1.223] [-3.405; 3.844] [-0.452; 0.800] [-0.263; 3.880] [-0.228; 0.276] [-0.136; 0.102] [-0.872; 0.553] [-2.548; 2.172] [-2.877; 2.776] [ 0.165; 2.433] [-0.595; 0.220]
LandOwned 0.312 2.722 0.197 0.627 -3.070 0.920 -0.081 1.951 -0.545 0.572 -1.356 0.760 0.938
  [-0.323; 0.947] [-0.445; 5.890] [-1.910; 2.304] [-1.557; 2.810] [-6.114; -0.025] [-7.001; 8.841] [-2.691; 2.528] [-0.515; 4.417] [-2.445; 1.355] [-1.865; 3.008] [-4.377; 1.664] [-1.475; 2.995] [-0.649; 2.525]
IndivOwner 0.289 0.846 -0.224 0.687 2.330 -1.286 0.417 -3.020   -0.831 -1.829 0.060 0.973
  [-0.200; 0.778] [-0.669; 2.361] [-1.878; 1.430] [-0.713; 2.086] [ 0.311; 4.349] [-4.805; 2.232] [-2.296; 3.130] [-6.366; 0.326]   [-4.767; 3.105] [-6.380; 2.722] [-1.648; 1.768] [-1.372; 3.318]
R2 0.008 0.063 0.133 0.034 0.143 0.333 0.058 0.075 0.045 0.071 0.071 0.061 0.032
Adj. R2 0.003 0.007 0.074 -0.037 0.074 0.083 0.001 0.015 0.004 0.030 -0.003 0.010 0.000
Num. obs. 1156 107 96 88 81 23 107 100 124 145 82 118 192






5.3.3 Parameter estimatess for CPT Model derived from mid-point approach (\(\gamma\))

  All Countries BJR2014 Austria Croatia France_I France_II Germany Italy Netherlands Poland Slovenia Spain Sweden
Constant 0.646 0.627 0.608 0.693 0.641 0.523 0.644 0.629 0.606 0.604 0.761 0.666 0.679
  [ 0.623; 0.669] [ 0.542; 0.713] [ 0.537; 0.678] [ 0.602; 0.783] [ 0.557; 0.724] [ 0.328; 0.719] [ 0.571; 0.718] [ 0.566; 0.692] [ 0.536; 0.675] [ 0.536; 0.671] [ 0.664; 0.858] [ 0.599; 0.734] [ 0.616; 0.743]
Age -0.000 0.007 0.002 -0.003 -0.009 0.003 0.004 0.005 0.000 0.003 0.003 0.002 -0.001
  [-0.002; 0.002] [-0.004; 0.017] [-0.004; 0.008] [-0.010; 0.005] [-0.017; -0.000] [-0.021; 0.027] [-0.003; 0.011] [ 0.000; 0.010] [-0.006; 0.007] [-0.004; 0.010] [-0.007; 0.012] [-0.004; 0.008] [-0.007; 0.005]
NbChildren -0.003 -0.012 0.076 -0.022 -0.115 -0.120 0.035 0.027 -0.047 0.015 -0.054 0.061 0.015
  [-0.024; 0.018] [-0.089; 0.065] [ 0.003; 0.148] [-0.121; 0.077] [-0.186; -0.043] [-0.293; 0.054] [-0.027; 0.098] [-0.018; 0.072] [-0.111; 0.017] [-0.043; 0.073] [-0.140; 0.032] [-0.031; 0.154] [-0.060; 0.089]
Trust 0.069 -0.072 0.235 0.133 0.094 -0.179 0.065 -0.111 0.033 -0.030 0.079 0.019 0.148
  [ 0.020; 0.117] [-0.273; 0.129] [ 0.086; 0.384] [-0.074; 0.341] [-0.115; 0.302] [-0.623; 0.265] [-0.085; 0.214] [-0.296; 0.075] [-0.112; 0.177] [-0.231; 0.171] [-0.143; 0.301] [-0.182; 0.219] [ 0.003; 0.294]
FarmSize 0.001 0.055 -0.030 0.300 -0.017 -0.220 0.012 0.003 0.042 -0.064 -0.027 -0.019 0.024
  [-0.009; 0.011] [-0.051; 0.160] [-0.095; 0.034] [-0.197; 0.797] [-0.082; 0.048] [-0.472; 0.032] [-0.016; 0.040] [-0.007; 0.012] [-0.034; 0.118] [-0.307; 0.179] [-0.363; 0.309] [-0.144; 0.107] [-0.024; 0.073]
LandOwned -0.005 0.040 0.062 0.008 0.113 -0.413 0.202 -0.173 0.078 0.014 -0.367 0.002 -0.036
  [-0.075; 0.064] [-0.408; 0.489] [-0.150; 0.274] [-0.291; 0.307] [-0.202; 0.428] [-1.378; 0.551] [-0.085; 0.488] [-0.372; 0.027] [-0.124; 0.280] [-0.236; 0.265] [-0.726; -0.007] [-0.246; 0.250] [-0.224; 0.152]
IndivOwner 0.012 0.044 -0.012 0.038 -0.215 0.106 0.168 0.127   -0.374 0.243 -0.073 -0.057
  [-0.041; 0.066] [-0.171; 0.258] [-0.178; 0.155] [-0.154; 0.229] [-0.424; -0.006] [-0.323; 0.534] [-0.129; 0.466] [-0.143; 0.397]   [-0.779; 0.030] [-0.299; 0.784] [-0.262; 0.117] [-0.335; 0.221]
R2 0.007 0.036 0.164 0.041 0.183 0.255 0.078 0.077 0.035 0.029 0.078 0.020 0.033
Adj. R2 0.002 -0.021 0.107 -0.030 0.117 -0.025 0.022 0.017 -0.006 -0.014 0.004 -0.033 0.002
Num. obs. 1156 107 96 88 81 23 107 100 124 145 82 118 192






6 Additional robustness checks discussed in main text

6.1 Reduced number of observations for the structural models

As in BJR2014, we re-estimated the structural models based on only observations next to the switching point. For example, if a respondent switched from A to B in lottery choice 7, we kept only the observations for lottery choices 6 and 7. If a respondent choose always lottery A or always lottery B, only one observation was kept.






6.1.1 Results over all samples for Expected Utility model (fewer observations per respondent)

  All Countries BJR2014 BJR2014 (weighted) Austria Croatia France_I France_II Germany Italy Netherlands Poland Slovenia Spain Sweden
r 0.225 0.255 0.266 0.225 0.196 0.236 0.256 0.216 0.220 0.262 0.230 0.207 0.191 0.235
  [0.219; 0.231] [0.235; 0.274] [0.242; 0.290] [0.204; 0.245] [0.173; 0.219] [0.213; 0.259] [0.219; 0.293] [0.200; 0.233] [0.200; 0.240] [0.246; 0.279] [0.214; 0.245] [0.185; 0.228] [0.168; 0.215] [0.219; 0.251]
LL (NULL) -4971.052 -335.481 -335.481 -457.122 -377.039 -324.308 -94.253 -550.155 -441.333 -546.003 -571.151 -403.912 -440.709 -762.525
LL (Converged) -4674.413 -302.558 -902.921 -433.508 -362.170 -301.733 -84.942 -521.061 -417.760 -490.928 -529.356 -385.702 -427.059 -710.454
Num. obs. 7182 487 487 662 544 469 136 794 640 790 824 583 638 1102
Num. resp. 1430 107 107 128 104 96 28 153 130 160 169 114 130 218
BIC 9357.704 611.304 1812.030 873.511 730.639 609.616 174.797 1048.800 841.981 988.527 1065.426 777.771 860.577 1427.913
AIC 9350.825 607.116 1807.842 869.016 726.340 605.465 171.884 1044.123 837.519 983.855 1060.712 773.403 856.118 1422.908
AICc 9350.826 607.124 1807.850 869.022 726.347 605.474 171.914 1044.128 837.525 983.860 1060.717 773.410 856.125 1422.912
Pseudo R2 0.060 0.098 -1.691 0.052 0.039 0.070 0.099 0.053 0.053 0.101 0.073 0.045 0.031 0.068






6.1.2 Results over all samples for Expected Utility model with covariates (fewer observations per respondent)

  All Countries BJR2014 Austria Croatia France_I France_II Germany Italy Netherlands Poland Slovenia Spain Sweden
r 0.224 0.254 0.209 0.190 0.243 0.261 0.216 0.218 0.256 0.232 0.203 0.186 0.232
  [ 0.218; 0.231] [ 0.234; 0.273] [ 0.163; 0.254] [ 0.165; 0.214] [ 0.217; 0.269] [ 0.226; 0.297] [ 0.198; 0.234] [ 0.195; 0.242] [ 0.237; 0.274] [ 0.216; 0.248] [ 0.176; 0.231] [ 0.160; 0.212] [ 0.216; 0.249]
Age 0.000 0.000 -0.002 0.001 -0.001 0.003 -0.000 0.000 -0.000 -0.001 0.001 -0.001 0.000
  [-0.000; 0.001] [-0.002; 0.002] [-0.005; 0.001] [-0.001; 0.003] [-0.004; 0.003] [-0.000; 0.006] [-0.002; 0.002] [-0.001; 0.002] [-0.002; 0.002] [-0.002; 0.001] [-0.003; 0.005] [-0.003; 0.001] [-0.001; 0.002]
NbChildren 0.006 -0.008 0.042 -0.005 -0.006 0.017 0.005 0.015 0.011 -0.004 0.012 -0.015 0.002
  [-0.001; 0.013] [-0.028; 0.012] [ 0.014; 0.070] [-0.031; 0.021] [-0.027; 0.015] [-0.004; 0.039] [-0.013; 0.023] [-0.002; 0.032] [-0.005; 0.026] [-0.019; 0.011] [-0.012; 0.036] [-0.045; 0.016] [-0.018; 0.022]
Trust 0.004 -0.011 -0.077 0.018 -0.008 -0.011 -0.035 -0.034 0.017 -0.001 -0.059 0.027 0.023
  [-0.010; 0.019] [-0.059; 0.037] [-0.166; 0.012] [-0.032; 0.069] [-0.099; 0.082] [-0.072; 0.050] [-0.075; 0.005] [-0.116; 0.048] [-0.019; 0.053] [-0.052; 0.049] [-0.147; 0.029] [-0.052; 0.107] [-0.018; 0.064]
FarmSize 0.001 -0.009 0.034 0.307 0.010 0.003 -0.004 0.001 0.007 0.043 -0.071 0.004 0.006
  [-0.000; 0.003] [-0.027; 0.010] [ 0.015; 0.052] [ 0.231; 0.384] [-0.003; 0.023] [-0.036; 0.041] [-0.010; 0.002] [-0.001; 0.002] [-0.003; 0.018] [-0.009; 0.096] [-0.192; 0.050] [-0.039; 0.046] [-0.008; 0.021]
LandOwned -0.023 0.070 -0.047 0.026 -0.041 -0.052 -0.107 0.004 -0.016 0.040 -0.017 -0.081 0.002
  [-0.043; -0.004] [-0.021; 0.161] [-0.127; 0.034] [-0.074; 0.127] [-0.137; 0.056] [-0.234; 0.130] [-0.190; -0.024] [-0.083; 0.091] [-0.065; 0.033] [-0.029; 0.110] [-0.103; 0.068] [-0.152; -0.011] [-0.054; 0.059]
LL (NULL) -4028.767 -335.481 -333.895 -325.775 -273.336 -76.173 -383.827 -350.980 -430.971 -489.317 -290.370 -396.637 -675.017
LL (Converged) -3788.039 -301.356 -311.911 -310.479 -251.866 -67.130 -359.958 -331.140 -390.922 -451.367 -276.500 -384.825 -630.497
Num. obs. 34932 2922 2910 2820 2370 660 3324 3048 3744 4236 2514 3450 5856
Num. resp. 1161 107 96 89 81 23 107 102 125 146 82 118 192
BIC 7638.845 650.593 671.676 668.626 550.356 173.214 768.570 710.414 831.211 952.841 599.979 818.526 1313.045
AIC 7588.078 614.713 635.821 632.959 515.732 146.261 731.916 674.280 793.843 914.733 565.001 781.649 1272.994
AICc 7588.080 614.742 635.850 632.989 515.767 146.390 731.942 674.308 793.866 914.753 565.034 781.674 1273.008
Pseudo R2 0.060 0.102 0.066 0.047 0.079 0.119 0.062 0.057 0.093 0.078 0.048 0.030 0.066







6.1.3 Results over all samples for Exponential Power model (fewer observations per respondent)

  All Countries BJR2014 BJR2014 (weighted) Austria Croatia France_I France_II Germany Italy Netherlands Poland Slovenia Spain Sweden
alpha 0.255 0.315 0.328 0.252 0.241 0.262 0.273 0.252 0.255 0.266 0.277 0.255 0.248 0.251
  [0.252; 0.259] [0.298; 0.331] [0.307; 0.349] [0.238; 0.265] [0.227; 0.256] [0.248; 0.275] [ 0.248; 0.299] [0.242; 0.263] [0.242; 0.268] [ 0.255; 0.278] [0.266; 0.288] [0.242; 0.268] [0.233; 0.264] [0.241; 0.262]
beta 0.070 0.076 0.070 0.061 0.098 0.066 0.043 0.075 0.075 0.010 0.089 0.108 0.119 0.041
  [0.062; 0.077] [0.062; 0.090] [0.054; 0.086] [0.037; 0.084] [0.069; 0.127] [0.032; 0.099] [-0.009; 0.094] [0.055; 0.095] [0.049; 0.101] [-0.011; 0.032] [0.071; 0.107] [0.081; 0.134] [0.091; 0.146] [0.020; 0.063]
LL (NULL) -4971.052 -335.481 -335.481 -457.122 -377.039 -324.308 -94.253 -550.155 -441.333 -546.003 -571.151 -403.912 -440.709 -762.525
LL (Converged) -4631.819 -288.254 -849.537 -430.525 -357.856 -298.941 -84.424 -515.631 -413.835 -490.774 -517.466 -378.608 -418.965 -708.273
Num. obs. 14364 974 974 1324 1088 938 272 1588 1280 1580 1648 1166 1276 2204
Num. resp. 1430 107 107 128 104 96 28 153 130 160 169 114 130 218
BIC 9282.783 590.270 1712.837 875.426 729.696 611.569 180.059 1046.002 841.979 996.278 1049.747 771.339 852.234 1431.943
AIC 9267.638 580.507 1703.075 865.049 719.712 601.882 172.847 1035.261 831.669 985.548 1038.932 761.217 841.931 1420.547
AICc 9267.638 580.520 1703.087 865.058 719.723 601.895 172.892 1035.269 831.679 985.555 1038.939 761.227 841.940 1420.552
Pseudo R2 0.068 0.141 -1.532 0.058 0.051 0.078 0.104 0.063 0.062 0.101 0.094 0.063 0.049 0.071







6.1.4 Results over all samples for Exponential Power model with covariates (fewer observations per respondent)

  All Countries BJR2014 Austria Croatia France_I Germany Italy Netherlands Poland Slovenia Spain Sweden
alpha 0.255 0.315 0.258 0.237 0.260 0.239 0.241 0.258 0.281 0.253 0.239 0.250
  [ 0.251; 0.260] [ 0.298; 0.332] [ 0.241; 0.274] [ 0.218; 0.256] [ 0.233; 0.287] [ 0.222; 0.255] [ 0.216; 0.267] [ 0.243; 0.274] [ 0.270; 0.293] [ 0.237; 0.268] [ 0.211; 0.267] [ 0.235; 0.265]
alpha_Age 0.000 0.000 -0.001 0.001 0.002 -0.001 0.001 -0.000 -0.000 0.001 -0.001 -0.000
  [-0.000; 0.000] [-0.001; 0.002] [-0.003; -0.000] [-0.002; 0.003] [-0.000; 0.005] [-0.002; 0.001] [-0.000; 0.003] [-0.002; 0.002] [-0.002; 0.001] [-0.001; 0.003] [-0.004; 0.001] [-0.002; 0.001]
alpha_NbChildren 0.004 -0.001 0.027 0.006 0.023 0.009 0.019 0.006 -0.001 -0.006 -0.002 -0.004
  [-0.001; 0.010] [-0.020; 0.018] [ 0.010; 0.045] [-0.021; 0.032] [ 0.000; 0.045] [-0.008; 0.026] [ 0.002; 0.036] [-0.008; 0.020] [-0.014; 0.012] [-0.024; 0.012] [-0.037; 0.033] [-0.020; 0.012]
alpha_Trust -0.015 0.003 -0.029 -0.019 0.090 -0.054 0.057 0.043 0.002 -0.008 -0.084 -0.011
  [-0.025; -0.005] [-0.039; 0.046] [-0.073; 0.015] [-0.062; 0.023] [ 0.019; 0.162] [-0.090; -0.019] [-0.014; 0.129] [ 0.001; 0.085] [-0.054; 0.058] [-0.051; 0.034] [-0.221; 0.053] [-0.053; 0.030]
alpha_FarmSize -0.009 -0.020 0.012 0.255 0.014 -0.016 -0.014 0.004 -0.005 -0.055 0.055 -0.006
  [-0.013; -0.005] [-0.037; -0.003] [-0.002; 0.026] [ 0.135; 0.376] [-0.014; 0.042] [-0.022; -0.010] [-0.018; -0.009] [-0.007; 0.015] [-0.054; 0.044] [-0.167; 0.056] [ 0.035; 0.076] [-0.056; 0.043]
alpha_LandOwned -0.019 0.003 0.011 -0.009 -0.076 -0.061 -0.006 -0.077 0.019 -0.031 -0.029 -0.009
  [-0.034; -0.004] [-0.088; 0.094] [-0.062; 0.085] [-0.092; 0.075] [-0.157; 0.006] [-0.144; 0.022] [-0.149; 0.136] [-0.146; -0.007] [-0.043; 0.081] [-0.083; 0.020] [-0.092; 0.034] [-0.105; 0.088]
beta 0.064 0.075 0.063 0.094 0.017 0.034 -0.001 -0.003 0.088 0.112 0.105 0.041
  [ 0.054; 0.075] [ 0.060; 0.091] [ 0.023; 0.104] [ 0.034; 0.155] [-0.053; 0.086] [-0.012; 0.080] [-0.095; 0.093] [-0.053; 0.046] [ 0.069; 0.107] [ 0.078; 0.147] [ 0.042; 0.168] [-0.006; 0.087]
beta_Age 0.000 -0.000 0.001 0.001 0.009 -0.000 0.001 0.000 0.001 0.001 0.002 -0.000
  [-0.001; 0.001] [-0.002; 0.001] [-0.002; 0.004] [-0.003; 0.004] [ 0.004; 0.013] [-0.003; 0.002] [-0.002; 0.005] [-0.002; 0.002] [-0.001; 0.003] [-0.004; 0.005] [-0.000; 0.004] [-0.003; 0.002]
beta_NbChildren -0.002 -0.001 0.000 0.007 0.046 -0.012 -0.005 -0.013 0.009 -0.040 0.032 -0.007
  [-0.010; 0.006] [-0.017; 0.016] [-0.019; 0.019] [-0.036; 0.050] [ 0.016; 0.076] [-0.033; 0.010] [-0.020; 0.011] [-0.028; 0.003] [-0.008; 0.027] [-0.093; 0.013] [-0.001; 0.066] [-0.042; 0.028]
beta_Trust -0.024 -0.005 0.032 -0.009 -0.008 0.032 -0.014 0.041 -0.008 0.104 -0.222 -0.058
  [-0.043; -0.004] [-0.043; 0.032] [-0.034; 0.099] [-0.130; 0.113] [-0.098; 0.081] [-0.028; 0.092] [-0.083; 0.055] [-0.028; 0.111] [-0.070; 0.054] [-0.029; 0.238] [-0.586; 0.142] [-0.117; 0.000]
beta_FarmSize -0.030 -0.001 -0.022 -0.127 0.008 -0.072 -0.130 -0.004 -0.086 0.044 0.002 -0.019
  [-0.047; -0.013] [-0.022; 0.021] [-0.044; -0.001] [-0.211; -0.043] [-0.028; 0.044] [-0.122; -0.022] [-0.275; 0.015] [-0.016; 0.008] [-0.205; 0.032] [-0.157; 0.245] [-0.028; 0.032] [-0.127; 0.088]
beta_LandOwned 0.010 -0.060 0.058 -0.009 -0.035 0.069 -0.019 -0.087 -0.036 0.007 0.082 -0.012
  [-0.015; 0.034] [-0.146; 0.026] [-0.064; 0.179] [-0.150; 0.133] [-0.238; 0.168] [-0.023; 0.161] [-0.186; 0.149] [-0.179; 0.005] [-0.101; 0.029] [-0.099; 0.112] [-0.047; 0.211] [-0.126; 0.101]
LL (NULL) -4028.767 -335.481 -333.895 -325.775 -273.336 -383.827 -350.980 -430.971 -489.317 -290.370 -396.637 -675.017
LL (Converged) -3745.410 -286.174 -307.437 -305.859 -246.688 -355.594 -326.602 -389.724 -440.022 -269.904 -375.866 -628.076
Num. obs. 69864 5844 5820 5640 4740 6648 6096 7488 8472 5028 6900 11712
Num. resp. 1161 107 96 89 81 107 102 125 146 82 118 192
BIC 7624.671 676.427 718.904 715.371 594.941 816.814 757.789 886.500 988.577 642.081 857.804 1368.572
AIC 7514.819 596.349 638.875 635.719 517.375 735.189 677.204 803.447 904.043 563.808 775.733 1280.152
AICc 7514.824 596.402 638.929 635.774 517.441 735.236 677.255 803.489 904.080 563.870 775.778 1280.179
Pseudo R2 0.070 0.147 0.079 0.061 0.097 0.074 0.069 0.096 0.101 0.070 0.052 0.070







6.1.5 Results over all samples for CPT model (fewer observations per respondent)

  All Countries BJR2014 BJR2014 (weighted) Austria Croatia France_I France_II Germany Italy Netherlands Poland Slovenia Spain Sweden
sigma 0.324 0.366 0.378 0.316 0.294 0.337 0.346 0.318 0.327 0.347 0.333 0.315 0.320 0.331
  [0.318; 0.329] [0.350; 0.381] [0.361; 0.394] [0.297; 0.335] [0.270; 0.317] [0.318; 0.357] [0.311; 0.382] [0.302; 0.333] [0.309; 0.345] [0.331; 0.364] [0.319; 0.347] [0.296; 0.335] [0.302; 0.338] [0.318; 0.345]
lambda 1.671 1.962 1.968 1.606 1.822 1.663 1.454 1.662 1.756 1.315 1.906 1.927 2.059 1.482
  [1.619; 1.723] [1.791; 2.134] [1.768; 2.168] [1.465; 1.748] [1.613; 2.031] [1.443; 1.882] [1.114; 1.795] [1.523; 1.802] [1.588; 1.924] [1.194; 1.436] [1.733; 2.080] [1.714; 2.140] [1.854; 2.265] [1.355; 1.609]
gamma 0.562 0.598 0.598 0.599 0.554 0.559 0.563 0.552 0.548 0.580 0.570 0.574 0.538 0.551
  [0.553; 0.570] [0.568; 0.628] [0.555; 0.641] [0.568; 0.631] [0.520; 0.588] [0.531; 0.588] [0.508; 0.617] [0.524; 0.580] [0.527; 0.570] [0.558; 0.602] [0.545; 0.595] [0.546; 0.603] [0.508; 0.569] [0.530; 0.572]
LL (NULL) -4971.052 -335.481 -335.481 -457.122 -377.039 -324.308 -94.253 -550.155 -441.333 -546.003 -571.151 -403.912 -440.709 -762.525
LL (Converged) -4268.420 -244.917 -673.203 -405.891 -340.850 -269.668 -75.558 -482.619 -377.934 -443.101 -471.396 -350.854 -377.291 -643.185
Num. obs. 21546 1461 1461 1986 1632 1407 408 2382 1920 2370 2472 1749 1914 3306
Num. resp. 1430 107 107 128 104 96 28 153 130 160 169 114 130 218
BIC 8566.774 511.694 1368.267 834.564 703.893 561.084 169.149 988.565 778.549 909.514 966.230 724.108 777.254 1310.680
AIC 8542.841 495.834 1352.407 817.783 687.700 545.336 157.115 971.238 761.869 892.202 948.792 707.708 760.583 1292.369
AICc 8542.842 495.850 1352.423 817.795 687.715 545.353 157.175 971.248 761.881 892.212 948.801 707.722 760.595 1292.377
Pseudo R2 0.141 0.270 -1.007 0.112 0.096 0.168 0.198 0.123 0.144 0.188 0.175 0.131 0.144 0.157







6.1.6 Results over all samples for CPT model with covariates (fewer observations per respondent)

  BJR2014 Austria France_I France_II Netherlands Poland Slovenia Spain Sweden
sigma 0.370 0.339 0.346 0.371 0.349 0.341 0.316 0.323 0.330
  [ 0.351; 0.388] [ 0.320; 0.359] [ 0.322; 0.371] [ 0.338; 0.405] [ 0.332; 0.366] [ 0.323; 0.358] [ 0.292; 0.339] [ 0.304; 0.343] [ 0.315; 0.345]
sigma_Age -0.001 -0.001 -0.001 -0.005 -0.001 -0.000 0.000 -0.002 0.000
  [-0.004; 0.001] [-0.002; 0.001] [-0.004; 0.002] [-0.008; -0.001] [-0.003; 0.001] [-0.002; 0.002] [-0.002; 0.003] [-0.004; -0.001] [-0.001; 0.002]
sigma_NbChildren 0.003 0.034 -0.009 -0.022 0.009 -0.004 -0.013 -0.020 0.009
  [-0.015; 0.020] [ 0.012; 0.056] [-0.030; 0.011] [-0.060; 0.017] [-0.009; 0.027] [-0.021; 0.014] [-0.037; 0.011] [-0.051; 0.011] [-0.009; 0.027]
sigma_Trust -0.001 0.037 -0.022 0.044 0.025 -0.008 -0.019 -0.032 0.027
  [-0.047; 0.045] [-0.005; 0.078] [-0.084; 0.040] [-0.060; 0.148] [-0.011; 0.060] [-0.067; 0.051] [-0.073; 0.035] [-0.086; 0.022] [-0.010; 0.065]
sigma_FarmSize -0.014 0.020 0.001 0.039 0.014 0.030 0.012 0.029 0.001
  [-0.031; 0.003] [ 0.004; 0.036] [-0.013; 0.015] [ 0.001; 0.077] [ 0.002; 0.026] [-0.068; 0.128] [-0.106; 0.130] [ 0.000; 0.058] [-0.011; 0.013]
sigma_LandOwned 0.023 0.039 0.019 -0.152 -0.037 0.018 -0.086 -0.049 0.011
  [-0.080; 0.126] [-0.025; 0.103] [-0.066; 0.103] [-0.350; 0.046] [-0.084; 0.010] [-0.056; 0.091] [-0.162; -0.010] [-0.131; 0.033] [-0.034; 0.056]
lambda 1.961 1.640 1.686 1.430 1.332 1.952 2.015 2.189 1.520
  [ 1.821; 2.101] [ 1.484; 1.797] [ 1.482; 1.891] [ 0.983; 1.876] [ 1.195; 1.469] [ 1.798; 2.107] [ 1.772; 2.257] [ 1.992; 2.386] [ 1.396; 1.644]
lambda_Age 0.001 -0.006 0.019 -0.047 0.005 0.015 0.016 0.005 0.006
  [-0.018; 0.019] [-0.019; 0.007] [-0.001; 0.039] [-0.121; 0.027] [-0.005; 0.016] [ 0.000; 0.031] [-0.010; 0.042] [-0.008; 0.018] [-0.005; 0.018]
lambda_NbChildren -0.033 0.184 0.019 -0.102 -0.053 0.035 -0.115 0.132 0.057
  [-0.155; 0.089] [ 0.040; 0.328] [-0.164; 0.202] [-0.842; 0.637] [-0.158; 0.051] [-0.098; 0.167] [-0.350; 0.121] [-0.093; 0.356] [-0.078; 0.193]
lambda_Trust -0.043 -0.026 -0.599 -0.101 0.029 0.049 0.622 -0.356 -0.302
  [-0.352; 0.266] [-0.335; 0.283] [-1.095; -0.103] [-1.545; 1.344] [-0.257; 0.315] [-0.466; 0.565] [-0.006; 1.250] [-0.936; 0.224] [-0.625; 0.021]
lambda_FarmSize -0.118 -0.024 -0.128 0.267 -0.082 -0.511 -0.083 0.475 -0.019
  [-0.290; 0.053] [-0.157; 0.109] [-0.256; 0.000] [-0.209; 0.743] [-0.207; 0.042] [-0.914; -0.108] [-0.541; 0.376] [ 0.106; 0.843] [-0.116; 0.077]
lambda_LandOwned -0.554 0.221 0.720 1.177 -0.434 -0.246 -0.207 0.698 0.018
  [-1.271; 0.163] [-0.277; 0.720] [-0.169; 1.609] [-2.934; 5.289] [-0.806; -0.062] [-0.830; 0.337] [-0.892; 0.477] [ 0.186; 1.209] [-0.346; 0.382]
gamma 0.596 0.607 0.574 0.571 0.567 0.569 0.585 0.531 0.551
  [ 0.562; 0.630] [ 0.571; 0.643] [ 0.540; 0.607] [ 0.537; 0.604] [ 0.540; 0.594] [ 0.540; 0.597] [ 0.552; 0.619] [ 0.497; 0.564] [ 0.528; 0.574]
gamma_Age 0.003 -0.003 0.001 0.004 -0.000 -0.000 -0.000 0.001 0.001
  [-0.001; 0.006] [-0.006; 0.000] [-0.003; 0.004] [ 0.001; 0.008] [-0.003; 0.002] [-0.004; 0.003] [-0.005; 0.004] [-0.001; 0.004] [-0.001; 0.003]
gamma_NbChildren -0.011 0.084 -0.001 0.079 0.003 -0.013 0.049 0.017 -0.009
  [-0.039; 0.016] [ 0.054; 0.115] [-0.030; 0.029] [ 0.034; 0.123] [-0.022; 0.028] [-0.038; 0.012] [ 0.013; 0.085] [-0.024; 0.057] [-0.037; 0.020]
gamma_Trust -0.002 -0.008 0.027 0.013 0.028 0.003 -0.036 0.016 0.013
  [-0.077; 0.072] [-0.080; 0.064] [-0.057; 0.111] [-0.077; 0.103] [-0.033; 0.089] [-0.092; 0.097] [-0.138; 0.066] [-0.080; 0.111] [-0.040; 0.067]
gamma_FarmSize -0.001 0.046 0.004 0.108 0.000 0.019 -0.095 0.024 0.003
  [-0.032; 0.031] [ 0.023; 0.070] [-0.038; 0.045] [ 0.052; 0.164] [-0.013; 0.013] [-0.044; 0.081] [-0.158; -0.031] [-0.012; 0.060] [-0.015; 0.020]
gamma_LandOwned -0.026 0.144 -0.077 0.197 -0.054 0.061 -0.069 0.048 -0.003
  [-0.195; 0.144] [ 0.032; 0.255] [-0.204; 0.050] [-0.053; 0.447] [-0.131; 0.022] [-0.039; 0.162] [-0.169; 0.032] [-0.062; 0.158] [-0.070; 0.064]
LL (NULL) -335.481 -333.895 -273.336 -76.173 -430.971 -489.317 -290.370 -396.637 -675.017
LL (Converged) -242.195 -277.441 -219.644 -53.235 -349.714 -396.756 -250.055 -331.435 -571.415
Num. obs. 8766 8730 7110 1980 11232 12708 7542 10350 17568
Num. resp. 107 96 81 23 125 146 82 118 192
BIC 647.806 718.223 598.934 243.105 867.306 963.612 660.819 829.276 1318.759
AIC 520.391 590.882 475.288 142.470 735.429 829.513 536.110 698.870 1178.830
AICc 520.469 590.960 475.384 142.819 735.490 829.566 536.201 698.937 1178.869
Pseudo R2 0.278 0.169 0.196 0.301 0.189 0.189 0.139 0.164 0.153






6.2 Excluding speeders

In this robustness check, we excluded respondents who completed the survey in six minutes or less. We arbitrarily selected this cut-off based on our own testing of the questionnaire. Note that we apply this test only to online data collection modes. In other words, the face-to-face data collections in Austria, Spain, and Italy are excluded from this robustness test.






6.2.1 Results over all samples for Expected Utility model (speeders removed)

  All Countries Croatia France_I France_II Germany Netherlands Poland Slovenia Sweden
r 0.223 0.228 0.186 0.187 0.232 0.240 0.216 0.211 0.232
  [0.214; 0.232] [0.201; 0.256] [0.140; 0.231] [0.119; 0.256] [0.211; 0.253] [0.218; 0.261] [0.191; 0.241] [0.178; 0.244] [0.214; 0.249]
LL (NULL) -23247.970 -2309.176 -2146.783 -638.889 -3437.312 -3554.902 -3705.444 -2446.225 -4968.972
LL (Converged) -22124.967 -2178.941 -2121.979 -623.350 -3246.627 -3376.248 -3531.590 -2350.250 -4674.464
Num. obs. 33660 3333 3135 924 4983 5214 5346 3531 7194
Num. resp. 1020 101 95 28 151 158 162 107 218
BIC 44260.359 4365.995 4252.009 1253.529 6501.768 6761.055 7071.764 4708.668 9357.810
AIC 44251.935 4359.883 4245.959 1248.700 6495.255 6754.496 7065.180 4702.499 9350.929
AICc 44251.935 4359.884 4245.960 1248.704 6495.255 6754.497 7065.181 4702.500 9350.929
Pseudo R2 0.048 0.056 0.012 0.024 0.055 0.050 0.047 0.039 0.059






6.2.2 Results over all samples for Expected Utility model with co-variates (speeders removed)

  All Countries Croatia France_I France_II Germany Netherlands Poland Slovenia Sweden
r 0.221 0.224 0.176 0.161 0.230 0.235 0.207 0.118 0.233
  [ 0.210; 0.231] [ 0.188; 0.260] [ 0.114; 0.238] [ 0.077; 0.244] [ 0.206; 0.255] [ 0.208; 0.261] [ 0.175; 0.240] [-0.001; 0.236] [ 0.214; 0.252]
Age 0.000 -0.001 0.003 0.006 0.001 -0.002 -0.002 -0.003 -0.000
  [-0.001; 0.001] [-0.005; 0.002] [-0.001; 0.007] [-0.003; 0.015] [-0.002; 0.004] [-0.004; 0.000] [-0.005; 0.001] [-0.010; 0.004] [-0.002; 0.002]
NbChildren 0.001 -0.015 0.011 0.025 0.003 -0.001 -0.010 0.067 -0.005
  [-0.008; 0.011] [-0.052; 0.021] [-0.025; 0.048] [-0.099; 0.149] [-0.018; 0.025] [-0.019; 0.017] [-0.037; 0.017] [ 0.014; 0.119] [-0.028; 0.018]
Trust 0.007 -0.038 0.059 0.124 0.003 0.010 -0.072 -0.077 -0.002
  [-0.015; 0.028] [-0.162; 0.086] [-0.028; 0.146] [-0.353; 0.601] [-0.051; 0.056] [-0.044; 0.063] [-0.193; 0.048] [-0.179; 0.025] [-0.043; 0.040]
FarmSize -0.004 0.042 0.010 0.079 0.002 0.009 0.029 0.273 -0.012
  [-0.015; 0.006] [-0.307; 0.391] [-0.026; 0.046] [-0.016; 0.173] [-0.008; 0.012] [-0.014; 0.031] [-0.052; 0.110] [ 0.060; 0.486] [-0.027; 0.003]
LandOwned -0.010 -0.039 -0.191 -0.115 0.014 -0.042 0.020 0.535 -0.010
  [-0.041; 0.021] [-0.114; 0.036] [-0.460; 0.078] [-0.591; 0.362] [-0.082; 0.110] [-0.117; 0.033] [-0.056; 0.097] [ 0.121; 0.948] [-0.065; 0.044]
LL (NULL) -18962.801 -1989.244 -1830.972 -524.104 -2387.050 -2794.475 -3223.480 -1804.497 -4373.276
LL (Converged) -18122.785 -1872.135 -1791.846 -499.521 -2262.617 -2675.186 -3078.431 -1721.752 -4105.265
Num. obs. 164934 17226 16038 4554 20790 24750 27918 15642 38016
Num. resp. 833 87 81 23 105 125 141 79 192
BIC 36317.649 3802.796 3641.789 1049.585 4584.887 5411.071 6218.284 3501.450 8273.805
AIC 36257.569 3756.271 3595.692 1011.043 4537.233 5362.372 6168.862 3455.504 8222.530
AICc 36257.570 3756.276 3595.697 1011.061 4537.237 5362.375 6168.865 3455.509 8222.532
Pseudo R2 0.044 0.059 0.021 0.047 0.052 0.043 0.045 0.046 0.061






6.2.3 Results over all samples for Exponential Power model (speeders removed)

  All Countries Croatia France_I France_II Germany Netherlands Poland Slovenia Sweden
alpha 0.224 0.252 0.198 0.206 0.231 0.201 0.240 0.237 0.213
  [ 0.213; 0.235] [0.222; 0.282] [ 0.157; 0.238] [ 0.133; 0.280] [ 0.205; 0.257] [ 0.177; 0.225] [0.214; 0.265] [0.207; 0.268] [ 0.186; 0.240]
beta 0.004 0.061 0.049 0.068 -0.004 -0.154 0.065 0.079 -0.062
  [-0.025; 0.033] [0.011; 0.112] [-0.081; 0.180] [-0.130; 0.265] [-0.075; 0.067] [-0.247; -0.061] [0.013; 0.117] [0.012; 0.147] [-0.147; 0.022]
LL (NULL) -23247.970 -2309.176 -2146.783 -638.889 -3437.312 -3554.902 -3705.444 -2446.225 -4968.972
LL (Converged) -22124.832 -2172.025 -2120.964 -622.629 -3246.604 -3353.914 -3522.252 -2341.795 -4668.515
Num. obs. 67320 6666 6270 1848 9966 10428 10692 7062 14388
Num. resp. 1020 101 95 28 151 158 162 107 218
BIC 44271.899 4361.660 4259.414 1260.302 6511.622 6726.333 7063.059 4701.314 9356.178
AIC 44253.665 4348.051 4245.927 1249.258 6497.208 6711.829 7048.504 4687.589 9341.029
AICc 44253.665 4348.053 4245.929 1249.265 6497.209 6711.830 7048.505 4687.591 9341.030
Pseudo R2 0.048 0.059 0.012 0.025 0.055 0.057 0.049 0.043 0.060






6.2.4 Results over all samples for Exponential Power model with covariates (speeders removed)

  All Countries Croatia France_I France_II Germany Netherlands Slovenia Sweden
alpha 0.219 0.200 0.174 0.200 0.216 0.200 0.200 0.198
  [ 0.206; 0.231] [ 0.092; 0.308] [ 0.076; 0.273] [ 0.113; 0.287] [ 0.177; 0.256] [ 0.153; 0.246] [ 0.104; 0.296] [ 0.164; 0.232]
alpha_Age -0.000 0.000 0.003 0.000 -0.000 -0.002 0.000 0.001
  [-0.001; 0.001] [-0.009; 0.009] [-0.001; 0.008] [-0.013; 0.013] [-0.004; 0.003] [-0.007; 0.003] [-0.006; 0.006] [-0.001; 0.003]
alpha_NbChildren 0.001 0.000 -0.010 0.000 -0.009 -0.014 0.000 -0.000
  [-0.008; 0.010] [-0.224; 0.224] [-0.035; 0.015] [-0.119; 0.119] [-0.032; 0.014] [-0.066; 0.038] [-0.039; 0.039] [-0.025; 0.024]
alpha_Trust -0.015 0.000 -0.011 0.000 -0.017 0.011 0.000 -0.054
  [-0.042; 0.012] [-0.199; 0.199] [-0.100; 0.077] [-0.225; 0.225] [-0.114; 0.080] [-0.081; 0.103] [-0.252; 0.252] [-0.096; -0.012]
alpha_FarmSize -0.027 0.000 -0.000 0.000 -0.009 -0.001 0.000 -0.043
  [-0.043; -0.010] [-0.354; 0.354] [-0.031; 0.030] [-0.141; 0.141] [-0.033; 0.015] [-0.046; 0.043] [-0.159; 0.159] [-0.088; 0.003]
alpha_LandOwned -0.021 0.000 0.101 0.000 0.123 -0.054 0.000 -0.040
  [-0.050; 0.009] [-0.184; 0.184] [-0.214; 0.415] [-0.390; 0.390] [-0.076; 0.321] [-0.213; 0.105] [-0.875; 0.875] [-0.102; 0.022]
beta -0.030 0.200 -0.129 0.200 -0.089 -0.158 0.200 -0.186
  [-0.072; 0.011] [-0.080; 0.480] [-0.615; 0.356] [-0.034; 0.434] [-0.244; 0.065] [-0.385; 0.069] [-0.076; 0.476] [-0.358; -0.013]
beta_Age -0.001 0.000 0.007 0.000 -0.003 0.000 0.000 0.001
  [-0.004; 0.001] [-0.025; 0.025] [-0.021; 0.035] [-0.027; 0.027] [-0.009; 0.003] [-0.016; 0.016] [-0.016; 0.016] [-0.005; 0.007]
beta_NbChildren -0.010 0.000 -0.092 0.000 -0.060 -0.063 0.000 -0.022
  [-0.037; 0.017] [-0.666; 0.666] [-0.259; 0.075] [-0.284; 0.284] [-0.170; 0.050] [-0.270; 0.143] [-0.090; 0.090] [-0.081; 0.037]
beta_Trust -0.074 0.000 -0.278 0.000 -0.043 -0.012 0.000 -0.178
  [-0.151; 0.003] [-0.572; 0.572] [-0.705; 0.149] [-0.561; 0.561] [-0.234; 0.147] [-0.358; 0.334] [-0.578; 0.578] [-0.306; -0.050]
beta_FarmSize -0.103 0.000 -0.052 0.000 -0.087 -0.041 0.000 -0.174
  [-0.174; -0.032] [-0.982; 0.982] [-0.138; 0.033] [-0.377; 0.377] [-0.390; 0.216] [-0.270; 0.188] [-0.365; 0.365] [-0.368; 0.020]
beta_LandOwned -0.045 0.000 0.643 0.000 0.229 -0.142 0.000 -0.178
  [-0.119; 0.030] [-0.448; 0.448] [ 0.003; 1.283] [-0.877; 0.877] [-0.455; 0.913] [-0.701; 0.417] [-2.227; 2.227] [-0.368; 0.013]
LL (NULL) -18962.801 -1989.244 -1830.972 -524.104 -2387.050 -2794.475 -1804.497 -4373.276
LL (Converged) -18061.280 -1907.621 -1772.473 -518.717 -2248.267 -2650.197 -1752.488 -4068.645
Num. obs. 329868 34452 32076 9108 41580 49500 31284 76032
Num. resp. 833 87 81 23 105 125 79 192
BIC 36275.038 3940.609 3669.457 1146.836 4624.159 5430.112 3629.187 8272.157
AIC 36146.560 3839.242 3568.946 1061.433 4520.535 5324.395 3528.977 8161.290
AICc 36146.561 3839.251 3568.956 1061.468 4520.542 5324.401 3528.987 8161.294
Pseudo R2 0.048 0.041 0.032 0.010 0.058 0.052 0.029 0.070






6.2.5 Results over all samples for CPT model (speeders removed)

  All Countries Croatia France_I France_II Germany Netherlands Poland Slovenia Sweden
sigma 0.319 0.331 0.292 0.284 0.334 0.316 0.305 0.326 0.329
  [0.312; 0.326] [0.310; 0.352] [0.258; 0.327] [0.232; 0.337] [0.319; 0.350] [0.297; 0.335] [0.286; 0.323] [0.303; 0.349] [0.315; 0.342]
lambda 1.565 1.804 1.725 1.751 1.554 1.213 1.761 1.859 1.352
  [1.482; 1.648] [1.555; 2.052] [1.385; 2.064] [1.074; 2.428] [1.366; 1.742] [1.007; 1.418] [1.517; 2.006] [1.585; 2.133] [1.185; 1.520]
gamma 0.579 0.593 0.565 0.562 0.576 0.622 0.600 0.565 0.552
  [0.557; 0.602] [0.531; 0.656] [0.468; 0.661] [0.401; 0.723] [0.521; 0.630] [0.562; 0.682] [0.534; 0.666] [0.500; 0.630] [0.506; 0.597]
LL (NULL) -23247.970 -2309.176 -2146.783 -638.889 -3437.312 -3554.902 -3705.444 -2446.225 -4968.972
LL (Converged) -20638.398 -1985.910 -2034.699 -597.967 -2960.594 -3222.859 -3334.674 -2141.389 -4254.937
Num. obs. 100980 9999 9405 2772 14949 15642 16038 10593 21582
Num. resp. 1020 101 95 28 151 158 162 107 218
BIC 41311.364 3999.450 4096.846 1219.715 5950.026 6474.692 6698.397 4310.582 8539.814
AIC 41282.796 3977.819 4075.399 1201.933 5927.188 6451.718 6675.349 4288.778 8515.875
AICc 41282.796 3977.822 4075.401 1201.942 5927.190 6451.720 6675.350 4288.780 8515.876
Pseudo R2 0.112 0.140 0.052 0.064 0.139 0.093 0.100 0.125 0.144






6.2.6 Results over all samples for CPT model with co-variates (speeders removed)

  All Countries Croatia France_I Germany Netherlands Poland Slovenia Sweden
sigma 0.318 0.336 0.292 0.337 0.316 0.292 0.318 0.329
  [ 0.312; 0.323] [ 0.322; 0.351] [ 0.271; 0.313] [ 0.323; 0.351] [ 0.301; 0.331] [ 0.275; 0.308] [ 0.301; 0.336] [ 0.318; 0.340]
sigma_Age -0.001 -0.002 0.000 0.000 -0.002 -0.002 -0.001 -0.001
  [-0.001; -0.000] [-0.003; -0.000] [-0.001; 0.002] [-0.001; 0.001] [-0.003; -0.000] [-0.004; -0.001] [-0.003; 0.001] [-0.002; -0.000]
sigma_NbChildren -0.005 -0.000 -0.011 -0.004 -0.019 0.002 -0.009 -0.002
  [-0.009; -0.000] [-0.018; 0.017] [-0.026; 0.004] [-0.015; 0.007] [-0.034; -0.004] [-0.010; 0.015] [-0.025; 0.006] [-0.013; 0.008]
sigma_Trust 0.015 0.028 0.049 0.039 0.007 -0.057 -0.003 -0.009
  [ 0.005; 0.026] [-0.002; 0.057] [ 0.006; 0.091] [ 0.012; 0.066] [-0.025; 0.039] [-0.131; 0.017] [-0.039; 0.033] [-0.032; 0.014]
sigma_FarmSize -0.006 -0.110 0.001 0.017 0.014 -0.051 0.135 -0.016
  [-0.012; 0.000] [-0.250; 0.029] [-0.013; 0.015] [ 0.004; 0.031] [-0.012; 0.040] [-0.107; 0.005] [ 0.081; 0.189] [-0.025; -0.007]
sigma_LandOwned -0.007 -0.052 -0.032 0.089 0.005 -0.036 0.099 -0.023
  [-0.023; 0.008] [-0.099; -0.006] [-0.107; 0.043] [ 0.039; 0.140] [-0.044; 0.054] [-0.076; 0.005] [ 0.000; 0.198] [-0.055; 0.008]
lambda 1.560 1.794 1.763 1.494 1.240 1.779 2.024 1.297
  [ 1.479; 1.641] [ 1.563; 2.026] [ 1.392; 2.134] [ 1.290; 1.698] [ 1.019; 1.462] [ 1.506; 2.053] [ 1.725; 2.324] [ 1.140; 1.453]
lambda_Age -0.007 -0.005 0.016 -0.007 0.006 -0.011 0.026 -0.008
  [-0.013; -0.001] [-0.022; 0.012] [-0.017; 0.050] [-0.024; 0.011] [-0.012; 0.025] [-0.038; 0.017] [-0.007; 0.059] [-0.022; 0.006]
lambda_NbChildren -0.047 0.020 0.113 -0.210 -0.082 0.117 -0.321 -0.121
  [-0.120; 0.027] [-0.200; 0.241] [-0.182; 0.408] [-0.358; -0.062] [-0.295; 0.130] [-0.085; 0.318] [-0.579; -0.062] [-0.285; 0.044]
lambda_Trust -0.246 -0.235 -0.314 0.116 -0.128 0.036 0.845 -0.400
  [-0.411; -0.080] [-0.634; 0.165] [-0.977; 0.348] [-0.270; 0.501] [-0.563; 0.307] [-1.185; 1.257] [ 0.155; 1.536] [-0.730; -0.069]
lambda_FarmSize -0.148 -2.211 -0.134 0.005 -0.224 -0.591 -0.517 -0.134
  [-0.235; -0.061] [-4.339; -0.083] [-0.389; 0.120] [-0.049; 0.059] [-0.439; -0.010] [-1.783; 0.600] [-1.149; 0.114] [-0.306; 0.039]
lambda_LandOwned 0.004 0.347 1.920 0.749 0.045 -0.329 -0.033 -0.342
  [-0.236; 0.243] [-0.216; 0.911] [ 0.427; 3.413] [-0.020; 1.518] [-0.564; 0.655] [-1.110; 0.452] [-1.392; 1.327] [-0.791; 0.107]
gamma 0.580 0.587 0.564 0.576 0.638 0.625 0.567 0.550
  [ 0.554; 0.606] [ 0.508; 0.666] [ 0.457; 0.672] [ 0.510; 0.641] [ 0.570; 0.706] [ 0.539; 0.711] [ 0.475; 0.659] [ 0.499; 0.602]
gamma_Age 0.001 0.000 0.009 -0.001 -0.000 -0.004 -0.003 0.002
  [-0.001; 0.003] [-0.005; 0.006] [ 0.000; 0.019] [-0.007; 0.005] [-0.006; 0.005] [-0.013; 0.005] [-0.010; 0.004] [-0.002; 0.006]
gamma_NbChildren 0.017 -0.034 0.059 0.005 0.058 -0.036 0.117 -0.013
  [-0.007; 0.041] [-0.092; 0.025] [-0.035; 0.153] [-0.051; 0.061] [-0.007; 0.122] [-0.102; 0.030] [ 0.044; 0.190] [-0.066; 0.039]
gamma_Trust -0.033 -0.102 0.060 -0.047 -0.006 -0.113 -0.047 -0.009
  [-0.086; 0.020] [-0.252; 0.048] [-0.133; 0.252] [-0.177; 0.082] [-0.137; 0.124] [-0.356; 0.130] [-0.234; 0.141] [-0.117; 0.100]
gamma_FarmSize -0.026 -0.023 0.004 -0.009 -0.045 0.290 -0.017 -0.032
  [-0.056; 0.004] [-0.997; 0.951] [-0.101; 0.109] [-0.025; 0.007] [-0.103; 0.012] [-0.106; 0.685] [-0.195; 0.162] [-0.085; 0.021]
gamma_LandOwned -0.003 0.031 -0.357 -0.004 -0.100 0.166 0.306 -0.012
  [-0.078; 0.071] [-0.127; 0.190] [-0.845; 0.132] [-0.241; 0.234] [-0.293; 0.093] [-0.047; 0.380] [-0.158; 0.771] [-0.140; 0.116]
LL (NULL) -18962.801 -1989.244 -1830.972 -2387.050 -2794.475 -3223.480 -1804.497 -4373.276
LL (Converged) -16874.744 -1655.066 -1701.652 -2026.042 -2529.287 -2899.330 -1546.031 -3696.122
Num. obs. 494802 51678 48114 62370 74250 83754 46926 114048
Num. resp. 833 87 81 105 125 141 79 192
BIC 33985.502 3505.482 3597.368 4250.820 5260.448 6002.702 3285.675 7601.843
AIC 33785.488 3346.132 3439.304 4088.085 5094.575 5834.661 3128.061 7428.244
AICc 33785.489 3346.145 3439.318 4088.096 5094.584 5834.669 3128.076 7428.250
Pseudo R2 0.110 0.168 0.071 0.151 0.095 0.101 0.143 0.155






6.3 Excluding uncertain and random respondents

As a robustness test, we excluded respondents who answered with “fully agree” to at least one of the statements “My choices were random.” and “It was difficult to understand the task.” (see section 7 for summary statistics on these questions).






6.3.1 Results over all samples for Expected Utility model (uncertain and random responses removed)

  All Countries Austria Croatia France_I France_II Germany Italy Netherlands Poland Slovenia Spain Sweden
r 0.217 0.232 0.240 0.174 0.184 0.227 0.199 0.243 0.218 0.205 0.135 0.236
  [0.208; 0.226] [0.202; 0.261] [0.214; 0.266] [0.116; 0.232] [0.111; 0.256] [0.205; 0.250] [0.168; 0.230] [0.221; 0.266] [0.193; 0.243] [0.171; 0.240] [0.075; 0.195] [0.217; 0.254]
LL (NULL) -28541.486 -2720.605 -1806.933 -1808.170 -615.770 -3201.131 -2471.118 -3128.102 -3476.697 -2420.199 -2317.516 -4468.839
LL (Converged) -27476.011 -2672.414 -1680.006 -1819.828 -602.197 -3046.529 -2461.210 -2981.434 -3305.651 -2338.567 -2313.308 -4181.463
Num. obs. 41514 4059 2607 2673 891 4653 3663 4620 5016 3498 3366 6468
Num. resp. 1258 123 79 81 27 141 111 140 152 106 102 196
BIC 54962.656 5353.137 3367.878 3647.547 1211.186 6101.503 4930.627 5971.307 6619.823 4685.294 4634.738 8371.701
AIC 54954.022 5346.828 3362.012 3641.656 1206.393 6095.058 4924.421 5964.869 6613.303 4679.134 4628.617 8364.927
AICc 54954.022 5346.829 3362.013 3641.657 1206.398 6095.058 4924.422 5964.870 6613.304 4679.136 4628.618 8364.927
Pseudo R2 0.037 0.018 0.070 -0.006 0.022 0.048 0.004 0.047 0.049 0.034 0.002 0.064

6.3.2 Results over all samples for Expected Utility model with co-variates (uncertain and random responses removed)

  All Countries Austria Croatia France_I France_II Germany Italy Netherlands Poland Slovenia Spain Sweden
r 0.213 0.224 0.239 0.159 0.161 0.221 0.194 0.236 0.208 0.099 0.015 0.235
  [ 0.203; 0.224] [ 0.176; 0.271] [ 0.208; 0.271] [ 0.072; 0.246] [ 0.077; 0.244] [ 0.195; 0.248] [ 0.124; 0.263] [ 0.208; 0.264] [ 0.175; 0.242] [-0.045; 0.242] [-0.361; 0.391] [ 0.216; 0.254]
Age -0.001 -0.002 -0.001 0.004 0.006 0.002 -0.003 -0.002 -0.002 -0.004 -0.005 -0.000
  [-0.001; 0.000] [-0.006; 0.002] [-0.004; 0.001] [-0.001; 0.009] [-0.003; 0.015] [-0.001; 0.004] [-0.006; -0.000] [-0.004; 0.000] [-0.005; 0.002] [-0.011; 0.004] [-0.020; 0.010] [-0.002; 0.002]
NbChildren 0.003 0.003 0.000 0.034 0.025 0.007 -0.006 0.007 -0.008 0.070 -0.079 -0.007
  [-0.007; 0.012] [-0.033; 0.040] [-0.026; 0.026] [-0.027; 0.095] [-0.099; 0.149] [-0.013; 0.028] [-0.032; 0.020] [-0.010; 0.025] [-0.039; 0.023] [ 0.013; 0.128] [-0.347; 0.189] [-0.031; 0.017]
Trust 0.011 -0.046 -0.057 0.118 0.124 -0.015 -0.129 -0.004 -0.113 -0.074 0.205 -0.006
  [-0.009; 0.032] [-0.141; 0.049] [-0.147; 0.033] [-0.002; 0.238] [-0.353; 0.601] [-0.068; 0.039] [-0.562; 0.304] [-0.059; 0.051] [-0.295; 0.069] [-0.195; 0.047] [-0.015; 0.426] [-0.049; 0.036]
FarmSize -0.003 0.025 0.083 0.030 0.079 -0.005 -0.006 -0.001 0.029 0.287 0.046 -0.012
  [-0.007; 0.001] [-0.005; 0.055] [-0.066; 0.233] [-0.016; 0.075] [-0.016; 0.173] [-0.016; 0.006] [-0.014; 0.002] [-0.057; 0.055] [-0.041; 0.100] [ 0.057; 0.517] [-0.079; 0.171] [-0.026; 0.003]
LandOwned 0.016 0.118 -0.008 -0.214 -0.115 -0.031 0.082 0.008 0.021 0.568 0.220 -0.011
  [-0.014; 0.046] [-0.077; 0.314] [-0.085; 0.069] [-0.486; 0.059] [-0.591; 0.362] [-0.124; 0.061] [-0.016; 0.181] [-0.074; 0.089] [-0.058; 0.099] [ 0.106; 1.030] [-0.216; 0.656] [-0.068; 0.045]
LL (NULL) -23042.202 -2033.836 -1486.800 -1540.633 -524.104 -2220.883 -2008.544 -2398.370 -3017.099 -1735.247 -2033.493 -3962.556
LL (Converged) -22272.958 -1976.172 -1369.528 -1526.912 -499.521 -2122.477 -1962.228 -2310.782 -2876.006 -1655.543 -2039.112 -3707.656
Num. obs. 201366 18216 12870 13662 4554 19404 17820 21384 26136 15048 17820 34452
Num. resp. 1017 92 65 69 23 98 90 108 132 76 90 174
BIC 44619.193 4011.204 2795.831 3110.959 1049.585 4304.193 3983.184 4681.387 5813.039 3368.801 4136.953 7477.995
AIC 44557.915 3964.343 2751.055 3065.825 1011.043 4256.953 3936.455 4633.564 5764.012 3323.087 4090.225 7427.311
AICc 44557.916 3964.348 2751.062 3065.831 1011.061 4256.958 3936.460 4633.568 5764.016 3323.092 4090.229 7427.314
Pseudo R2 0.033 0.028 0.079 0.009 0.047 0.044 0.023 0.037 0.047 0.046 -0.003 0.064






6.3.3 Results over all samples for Expected Utility expo power model (uncertain and random responses removed)

  All Countries Austria Croatia France_I France_II Germany Italy Netherlands Poland Slovenia Spain Sweden
alpha 0.213 0.211 0.264 0.178 0.202 0.219 0.174 0.195 0.240 0.228 0.192 0.213
  [ 0.203; 0.224] [ 0.183; 0.239] [0.233; 0.295] [ 0.128; 0.228] [ 0.124; 0.279] [ 0.191; 0.247] [ 0.135; 0.214] [ 0.173; 0.217] [0.213; 0.266] [ 0.193; 0.262] [0.143; 0.241] [ 0.185; 0.242]
beta -0.013 -0.089 0.056 0.016 0.065 -0.028 -0.125 -0.204 0.058 0.071 0.217 -0.074
  [-0.044; 0.018] [-0.198; 0.020] [0.009; 0.103] [-0.171; 0.202] [-0.154; 0.283] [-0.116; 0.060] [-0.286; 0.036] [-0.290; -0.118] [0.004; 0.112] [-0.007; 0.150] [0.083; 0.350] [-0.164; 0.016]
LL (NULL) -28541.486 -2720.605 -1806.933 -1808.170 -615.770 -3201.131 -2471.118 -3128.102 -3476.697 -2420.199 -2317.516 -4468.839
LL (Converged) -27474.668 -2666.233 -1673.897 -1819.776 -601.636 -3045.674 -2456.280 -2946.727 -3298.685 -2333.330 -2293.585 -4173.802
Num. obs. 83028 8118 5214 5346 1782 9306 7326 9240 10032 6996 6732 12936
Num. resp. 1258 123 79 81 27 141 111 140 152 106 102 196
BIC 54971.990 5350.469 3364.912 3656.720 1218.243 6109.626 4930.358 5911.717 6615.797 4684.366 4604.799 8366.540
AIC 54953.336 5336.466 3351.794 3643.552 1207.272 6095.349 4916.559 5897.455 6601.370 4670.660 4591.169 8351.604
AICc 54953.336 5336.467 3351.796 3643.554 1207.279 6095.350 4916.561 5897.456 6601.371 4670.662 4591.171 8351.605
Pseudo R2 0.037 0.020 0.074 -0.006 0.023 0.049 0.006 0.058 0.051 0.036 0.010 0.066






6.3.4 Results over all samples for Expected Utility expo power model with co-variates (uncertain and random responses removed)

  All Countries Austria Croatia France_II Germany Italy Netherlands Spain Sweden
alpha 0.208 0.139 0.200 0.200 0.198 0.153 0.200 0.068 0.195
  [ 0.196; 0.220] [ 0.065; 0.214] [-0.092; 0.492] [ 0.113; 0.287] [ 0.152; 0.243] [ 0.103; 0.202] [-0.334; 0.735] [-0.200; 0.336] [ 0.164; 0.225]
alpha_Age -0.001 -0.000 0.000 0.000 0.000 -0.006 -0.003 0.001 0.001
  [-0.001; 0.000] [-0.003; 0.002] [-0.039; 0.039] [-0.013; 0.013] [-0.003; 0.003] [-0.008; -0.003] [-0.116; 0.111] [-0.004; 0.007] [-0.002; 0.003]
alpha_NbChildren 0.003 -0.007 0.000 0.000 -0.011 -0.047 0.000 0.023 0.005
  [-0.006; 0.012] [-0.019; 0.006] [-1.076; 1.076] [-0.119; 0.119] [-0.031; 0.008] [-0.086; -0.008] [-0.575; 0.575] [-0.020; 0.065] [-0.021; 0.031]
alpha_Trust -0.019 0.013 0.000 0.000 -0.032 -0.094 0.000 0.137 -0.077
  [-0.045; 0.008] [-0.063; 0.089] [-2.089; 2.089] [-0.225; 0.225] [-0.083; 0.019] [-0.231; 0.042] [-1.373; 1.373] [-0.091; 0.366] [-0.116; -0.038]
alpha_FarmSize -0.020 0.067 0.000 0.000 -0.011 -0.003 -0.000 0.028 -0.041
  [-0.032; -0.009] [ 0.040; 0.093] [-0.639; 0.639] [-0.141; 0.141] [-0.015; -0.008] [-0.009; 0.003] [-0.198; 0.198] [ 0.011; 0.046] [-0.069; -0.013]
alpha_LandOwned -0.009 0.427 0.000 0.000 0.120 0.148 0.000 0.354 -0.026
  [-0.040; 0.023] [ 0.187; 0.666] [-1.085; 1.085] [-0.390; 0.390] [-0.039; 0.279] [-0.005; 0.301] [-2.414; 2.414] [-0.388; 1.095] [-0.077; 0.025]
beta -0.050 -0.410 0.200 0.200 -0.180 -0.318 0.200 0.682 -0.210
  [-0.093; -0.007] [-0.803; -0.016] [-0.633; 1.033] [-0.034; 0.434] [-0.393; 0.033] [-0.641; 0.004] [-0.754; 1.154] [-0.289; 1.652] [-0.355; -0.066]
beta_Age -0.001 -0.002 0.000 0.000 -0.006 -0.013 0.007 -0.022 -0.002
  [-0.003; 0.002] [-0.010; 0.005] [-0.081; 0.081] [-0.027; 0.027] [-0.013; 0.002] [-0.021; -0.004] [-0.237; 0.251] [-0.059; 0.015] [-0.007; 0.004]
beta_NbChildren -0.007 0.019 0.000 0.000 -0.096 -0.155 -0.000 -0.283 -0.021
  [-0.033; 0.018] [-0.036; 0.073] [-2.780; 2.780] [-0.284; 0.284] [-0.218; 0.026] [-0.387; 0.077] [-1.260; 1.259] [-0.827; 0.260] [-0.087; 0.045]
beta_Trust -0.096 0.233 0.000 0.000 -0.005 -0.386 -0.000 -0.556 -0.216
  [-0.181; -0.011] [-0.020; 0.487] [-5.073; 5.073] [-0.561; 0.561] [-0.209; 0.200] [-0.711; -0.060] [-2.901; 2.901] [-1.988; 0.876] [-0.353; -0.079]
beta_FarmSize -0.114 0.125 0.000 0.000 -0.117 0.037 0.000 0.016 -0.161
  [-0.173; -0.055] [-0.010; 0.259] [-1.776; 1.776] [-0.377; 0.377] [-0.190; -0.044] [-0.167; 0.240] [-0.355; 0.355] [-0.032; 0.064] [-0.306; -0.015]
beta_LandOwned -0.081 1.622 0.000 0.000 0.363 0.173 -0.000 -0.013 -0.106
  [-0.163; 0.002] [ 0.395; 2.848] [-2.283; 2.283] [-0.877; 0.877] [-0.253; 0.979] [-0.398; 0.744] [-5.693; 5.693] [-3.647; 3.621] [-0.257; 0.044]
LL (NULL) -23042.202 -2033.836 -1486.800 -524.104 -2220.883 -2008.544 -2398.370 -2033.493 -3962.556
LL (Converged) -22206.291 -1930.012 -1413.315 -518.717 -2100.480 -1940.916 -2409.477 -2007.802 -3667.476
Num. obs. 402732 36432 25740 9108 38808 35640 42768 35640 68904
Num. resp. 1017 92 65 23 98 90 108 90 174
BIC 44567.455 3986.063 2948.500 1146.836 4327.756 4007.607 4946.917 4141.378 7468.637
AIC 44436.582 3884.024 2850.630 1061.433 4224.959 3905.832 4842.955 4039.604 7358.951
AICc 44436.583 3884.033 2850.643 1061.468 4224.967 3905.841 4842.962 4039.613 7358.956
Pseudo R2 0.036 0.051 0.049 0.010 0.054 0.034 -0.005 0.013 0.074






6.3.5 Results over all samples for CPT model (uncertain and random responses removed)

  All Countries Austria Croatia France_I France_II Germany Italy Netherlands Poland Slovenia Spain Sweden
sigma 0.314 0.322 0.337 0.286 0.276 0.331 0.302 0.314 0.301 0.320 0.279 0.332
  [0.307; 0.321] [0.296; 0.348] [0.315; 0.358] [0.242; 0.329] [0.220; 0.332] [0.314; 0.347] [0.273; 0.331] [0.293; 0.336] [0.281; 0.321] [0.296; 0.345] [0.242; 0.315] [0.318; 0.346]
lambda 1.539 1.507 1.794 1.651 1.736 1.491 1.350 1.082 1.731 1.810 2.189 1.317
  [1.462; 1.615] [1.287; 1.726] [1.529; 2.058] [1.275; 2.027] [1.004; 2.468] [1.295; 1.687] [1.060; 1.639] [0.859; 1.305] [1.474; 1.987] [1.528; 2.092] [1.815; 2.564] [1.146; 1.488]
gamma 0.577 0.641 0.613 0.552 0.570 0.564 0.542 0.632 0.617 0.560 0.476 0.551
  [0.556; 0.598] [0.574; 0.707] [0.547; 0.679] [0.439; 0.664] [0.390; 0.749] [0.504; 0.623] [0.480; 0.605] [0.565; 0.699] [0.546; 0.688] [0.493; 0.628] [0.374; 0.578] [0.503; 0.599]
LL (NULL) -28541.486 -2720.605 -1806.933 -1808.170 -615.770 -3201.131 -2471.118 -3128.102 -3476.697 -2420.199 -2317.516 -4468.839
LL (Converged) -25864.112 -2560.315 -1525.117 -1758.472 -582.142 -2789.148 -2340.178 -2857.381 -3146.146 -2154.781 -2180.335 -3776.805
Num. obs. 124542 12177 7821 8019 2673 13959 10989 13860 15048 10494 10098 19404
Num. resp. 1258 123 79 81 27 141 111 140 152 106 102 196
BIC 51763.422 5148.852 3077.128 3543.913 1187.957 5606.929 4708.270 5743.373 6321.148 4337.337 4388.330 7583.231
AIC 51734.225 5126.630 3056.234 3522.944 1170.284 5584.297 4686.356 5720.763 6298.291 4315.561 4366.669 7559.611
AICc 51734.225 5126.632 3056.237 3522.947 1170.293 5584.299 4686.358 5720.765 6298.293 4315.563 4366.672 7559.612
Pseudo R2 0.094 0.059 0.156 0.027 0.055 0.129 0.053 0.087 0.095 0.110 0.059 0.155






6.3.6 Results over all samples for CPT model with co-variates (uncertain and random responses removed)

  All Countries Austria Croatia France_I Italy Netherlands Poland Slovenia Spain Sweden
sigma 0.310 0.316 0.346 0.261 0.279 0.315 0.283 0.316 0.241 0.330
  [ 0.305; 0.315] [ 0.297; 0.334] [ 0.331; 0.361] [ 0.229; 0.292] [ 0.233; 0.325] [ 0.298; 0.332] [ 0.262; 0.303] [ 0.298; 0.334] [ 0.206; 0.276] [ 0.318; 0.342]
sigma_Age -0.001 -0.000 -0.002 0.002 -0.002 -0.002 -0.003 -0.000 -0.002 -0.001
  [-0.001; -0.000] [-0.002; 0.001] [-0.003; -0.000] [-0.001; 0.004] [-0.003; -0.000] [-0.003; -0.000] [-0.004; -0.001] [-0.002; 0.002] [-0.005; 0.001] [-0.002; -0.000]
sigma_NbChildren -0.003 -0.004 0.012 0.003 0.000 -0.011 -0.001 -0.007 -0.001 -0.001
  [-0.008; 0.001] [-0.025; 0.017] [-0.005; 0.030] [-0.021; 0.027] [-0.019; 0.019] [-0.026; 0.003] [-0.015; 0.013] [-0.023; 0.009] [-0.037; 0.036] [-0.013; 0.011]
sigma_Trust 0.019 -0.012 0.013 0.116 -0.034 0.001 -0.119 -0.009 0.111 -0.011
  [ 0.008; 0.030] [-0.056; 0.033] [-0.025; 0.052] [ 0.059; 0.173] [-0.111; 0.043] [-0.034; 0.036] [-0.248; 0.011] [-0.048; 0.031] [ 0.053; 0.170] [-0.035; 0.013]
sigma_FarmSize -0.009 0.014 0.009 0.026 -0.045 -0.008 -0.047 0.140 0.018 -0.016
  [-0.014; -0.005] [-0.003; 0.032] [-0.083; 0.100] [ 0.007; 0.046] [-0.095; 0.005] [-0.029; 0.013] [-0.103; 0.010] [ 0.086; 0.195] [-0.010; 0.045] [-0.026; -0.007]
sigma_LandOwned 0.005 0.091 -0.036 -0.096 0.003 0.048 -0.047 0.114 0.156 -0.032
  [-0.010; 0.020] [ 0.024; 0.158] [-0.096; 0.024] [-0.187; -0.004] [-0.041; 0.047] [-0.010; 0.106] [-0.088; -0.007] [ 0.014; 0.214] [ 0.032; 0.280] [-0.066; 0.001]
lambda 1.516 1.493 1.793 1.588 1.244 1.080 1.708 1.986 2.374 1.264
  [ 1.435; 1.596] [ 1.217; 1.769] [ 1.553; 2.033] [ 0.993; 2.183] [ 0.402; 2.087] [ 0.822; 1.338] [ 1.323; 2.093] [ 1.671; 2.301] [ 1.758; 2.991] [ 1.099; 1.429]
lambda_Age -0.004 0.004 -0.004 0.041 -0.007 0.008 -0.013 0.020 -0.001 -0.010
  [-0.010; 0.002] [-0.013; 0.022] [-0.025; 0.017] [-0.000; 0.083] [-0.026; 0.013] [-0.017; 0.033] [-0.040; 0.014] [-0.011; 0.052] [-0.046; 0.044] [-0.026; 0.005]
lambda_NbChildren -0.044 -0.014 0.052 0.220 0.029 -0.159 0.093 -0.328 0.063 -0.107
  [-0.116; 0.028] [-0.235; 0.208] [-0.163; 0.266] [-0.206; 0.646] [-0.217; 0.275] [-0.401; 0.083] [-0.115; 0.300] [-0.580; -0.076] [-0.555; 0.682] [-0.273; 0.059]
lambda_Trust -0.220 0.010 -0.091 -0.076 0.025 0.078 -0.219 0.654 -0.793 -0.414
  [-0.379; -0.062] [-0.481; 0.500] [-0.622; 0.440] [-0.921; 0.769] [-0.998; 1.048] [-0.398; 0.555] [-2.854; 2.417] [-0.064; 1.371] [-1.832; 0.245] [-0.758; -0.070]
lambda_FarmSize -0.192 -0.256 -1.116 -0.105 -0.156 -0.549 -0.356 -0.597 -0.242 -0.090
  [-0.284; -0.100] [-0.425; -0.087] [-2.458; 0.225] [-0.354; 0.144] [-1.045; 0.733] [-1.005; -0.092] [-1.551; 0.838] [-1.245; 0.051] [-0.663; 0.178] [-0.263; 0.083]
lambda_LandOwned -0.025 0.126 0.290 1.526 -0.495 -0.240 -0.299 -0.197 1.262 -0.140
  [-0.258; 0.207] [-1.055; 1.307] [-0.385; 0.965] [-0.333; 3.385] [-1.215; 0.225] [-0.955; 0.476] [-1.069; 0.471] [-1.595; 1.202] [-0.868; 3.391] [-0.608; 0.329]
gamma 0.575 0.659 0.603 0.551 0.626 0.619 0.649 0.559 0.360 0.554
  [ 0.550; 0.601] [ 0.568; 0.749] [ 0.526; 0.681] [ 0.381; 0.721] [ 0.395; 0.858] [ 0.544; 0.694] [ 0.544; 0.753] [ 0.459; 0.659] [ 0.190; 0.530] [ 0.500; 0.609]
gamma_Age -0.001 -0.005 -0.002 0.017 -0.005 -0.001 0.000 -0.003 -0.003 0.002
  [-0.002; 0.001] [-0.011; 0.000] [-0.009; 0.004] [ 0.004; 0.030] [-0.009; -0.002] [-0.008; 0.005] [-0.010; 0.010] [-0.011; 0.005] [-0.011; 0.006] [-0.002; 0.007]
gamma_NbChildren 0.016 0.011 -0.004 0.223 -0.040 0.047 -0.044 0.110 -0.050 -0.014
  [-0.008; 0.039] [-0.069; 0.091] [-0.057; 0.049] [ 0.095; 0.350] [-0.126; 0.046] [-0.020; 0.114] [-0.111; 0.022] [ 0.038; 0.182] [-0.168; 0.068] [-0.069; 0.041]
gamma_Trust -0.027 -0.185 -0.184 0.201 0.030 0.003 -0.144 -0.068 0.197 -0.016
  [-0.076; 0.022] [-0.323; -0.047] [-0.358; -0.010] [-0.048; 0.450] [-0.065; 0.124] [-0.145; 0.152] [-0.620; 0.333] [-0.269; 0.134] [ 0.022; 0.371] [-0.131; 0.098]
gamma_FarmSize -0.006 0.058 0.264 0.051 0.077 -0.106 0.310 -0.004 0.032 -0.018
  [-0.038; 0.027] [-0.010; 0.126] [-0.428; 0.955] [-0.052; 0.154] [-0.168; 0.321] [-0.210; -0.003] [-0.094; 0.713] [-0.181; 0.174] [-0.056; 0.121] [-0.073; 0.038]
gamma_LandOwned 0.064 0.039 0.084 -0.373 0.288 -0.062 0.135 0.280 0.409 0.024
  [-0.007; 0.135] [-0.364; 0.442] [-0.090; 0.259] [-1.090; 0.344] [ 0.129; 0.447] [-0.280; 0.155] [-0.083; 0.353] [-0.172; 0.732] [-0.225; 1.042] [-0.119; 0.168]
LL (NULL) -23042.202 -2033.836 -1486.800 -1540.633 -2008.544 -2398.370 -3017.099 -1735.247 -2033.493 -3962.556
LL (Converged) -20939.505 -1880.893 -1195.771 -1457.598 -1823.537 -2182.578 -2719.576 -1496.524 -1932.991 -3329.366
Num. obs. 604098 54648 38610 40986 53460 64152 78408 45144 53460 103356
Num. resp. 1017 92 65 69 90 108 132 76 90 174
BIC 42118.617 3958.142 2581.645 3106.373 3843.035 4564.397 5642.007 3185.965 4061.943 6866.558
AIC 41915.011 3797.786 2427.542 2951.195 3683.075 4401.155 5475.152 3029.048 3901.982 6694.731
AICc 41915.012 3797.798 2427.560 2951.212 3683.087 4401.166 5475.161 3029.063 3901.995 6694.738
Pseudo R2 0.091 0.075 0.196 0.054 0.092 0.090 0.099 0.138 0.049 0.160






7 Follow-up comprehension and assessment questions

Directly after the lottery choices, participants responded to three items on their comprehension and attitude towards the survey. Responses are on a 5-point scale ranging from strongly disagree to strongly agree.






7.1 Self-assessed difficulty in understanding the task

Country It was difficult to
understand the task 		Total (2.63)
Stongly Disagree Disagree Neither nor Agree Strongly Agree
Austria
(2.3) 		34
28.1 % 		46
38 % 		15
12.4 % 		23
19 % 		3
2.5 % 		121
100 %
Croatia
(2.75) 		16
15.7 % 		35
34.3 % 		20
19.6 % 		20
19.6 % 		11
10.8 % 		102
100 %
France_I
(2.47) 		33
35.1 % 		19
20.2 % 		15
16 % 		19
20.2 % 		8
8.5 % 		94
100 %
France_II
(2.29) 		8
28.6 % 		10
35.7 % 		5
17.9 % 		4
14.3 % 		1
3.6 % 		28
100 %
Germany
(2.44) 		31
20.4 % 		59
38.8 % 		31
20.4 % 		26
17.1 % 		5
3.3 % 		152
100 %
Italy
(2.52) 		32
25.8 % 		41
33.1 % 		16
12.9 % 		24
19.4 % 		11
8.9 % 		124
100 %
Netherlands

(2.63) 		24
15.9 % 		60
39.7 % 		28
18.5 % 		26
17.2 % 		13
8.6 % 		151
100 %
Poland
(2.51) 		29
17.2 % 		72
42.6 % 		32
18.9 % 		25
14.8 % 		11
6.5 % 		169
100 %
Slovenia
(2.73) 		11
9.7 % 		40
35.4 % 		36
31.9 % 		21
18.6 % 		5
4.4 % 		113
100 %
Spain
(3.57) 		8
6.2 % 		18
14 % 		21
16.3 % 		56
43.4 % 		26
20.2 % 		129
100 %
Sweden
(2.57) 		43
20.1 % 		80
37.4 % 		36
16.8 % 		36
16.8 % 		19
8.9 % 		214
100 %
Total (2.63) 269
19.3 % 		480
34.4 % 		255
18.3 % 		280
20 % 		113
8.1 % 		1397
100 %






7.2 Self-assessed randomness of lottery choices

Country My choices were
random 		Total (2.34)
Stongly Disagree Disagree Neither nor Agree Strongly Agree
Austria
(2.24) 		33
26.8 % 		51
41.5 % 		20
16.3 % 		15
12.2 % 		4
3.3 % 		123
100 %
Croatia
(2.96) 		18
17.5 % 		27
26.2 % 		18
17.5 % 		21
20.4 % 		19
18.4 % 		103
100 %
France_I
(2.16) 		44
46.3 % 		20
21.1 % 		13
13.7 % 		8
8.4 % 		10
10.5 % 		95
100 %
France_II
(1.75) 		15
53.6 % 		8
28.6 % 		3
10.7 % 		1
3.6 % 		1
3.6 % 		28
100 %
Germany
(2.41) 		36
23.5 % 		62
40.5 % 		21
13.7 % 		25
16.3 % 		9
5.9 % 		153
100 %
Italy
(2.44) 		40
32.3 % 		39
31.5 % 		7
5.6 % 		27
21.8 % 		11
8.9 % 		124
100 %
Netherlands

(2.33) 		39
25.5 % 		66
43.1 % 		16
10.5 % 		22
14.4 % 		10
6.5 % 		153
100 %
Poland
(2.21) 		54
32.3 % 		59
35.3 % 		27
16.2 % 		19
11.4 % 		8
4.8 % 		167
100 %
Slovenia
(2.54) 		23
20.2 % 		41
36 % 		22
19.3 % 		22
19.3 % 		6
5.3 % 		114
100 %
Spain
(2.25) 		38
29.5 % 		45
34.9 % 		25
19.4 % 		18
14 % 		3
2.3 % 		129
100 %
Sweden
(2.21) 		64
29.8 % 		89
41.4 % 		24
11.2 % 		28
13 % 		10
4.7 % 		215
100 %
Total (2.34) 404
28.8 % 		507
36.1 % 		196
14 % 		206
14.7 % 		91
6.5 % 		1404
100 %






7.3 Self-assessment of number of lottery choices

Country There were too many
different lotteries 		Total (2.61)
Stongly Disagree Disagree Neither nor Agree Strongly Agree
Austria
(2.23) 		43
35 % 		35
28.5 % 		23
18.7 % 		18
14.6 % 		4
3.3 % 		123
100 %
Croatia
(2.68) 		15
14.7 % 		32
31.4 % 		35
34.3 % 		11
10.8 % 		9
8.8 % 		102
100 %
France_I
(2.62) 		27
29 % 		17
18.3 % 		21
22.6 % 		20
21.5 % 		8
8.6 % 		93
100 %
France_II
(2.63) 		6
22.2 % 		3
11.1 % 		14
51.9 % 		3
11.1 % 		1
3.7 % 		27
100 %
Germany
(2.35) 		39
25.7 % 		55
36.2 % 		31
20.4 % 		20
13.2 % 		7
4.6 % 		152
100 %
Italy
(2.6) 		28
23 % 		37
30.3 % 		22
18 % 		26
21.3 % 		9
7.4 % 		122
100 %
Netherlands

(2.53) 		29
19.3 % 		56
37.3 % 		28
18.7 % 		31
20.7 % 		6
4 % 		150
100 %
Poland
(2.48) 		40
24 % 		52
31.1 % 		40
24 % 		25
15 % 		10
6 % 		167
100 %
Slovenia
(2.43) 		20
18 % 		37
33.3 % 		41
36.9 % 		12
10.8 % 		1
0.9 % 		111
100 %
Spain
(3.5) 		4
3.1 % 		14
10.9 % 		46
35.7 % 		44
34.1 % 		21
16.3 % 		129
100 %
Sweden
(2.68) 		34
16.7 % 		56
27.6 % 		66
32.5 % 		34
16.7 % 		13
6.4 % 		203
100 %
Total (2.61) 285
20.7 % 		394
28.6 % 		367
26.6 % 		244
17.7 % 		89
6.5 % 		1379
100 %






8 Screenshots of survey instrument (example)

9 Additional resources

The paper, this appendix and all other material are publicly available on the open science framework (OSF) webpage https://osf.io/hvmj6/. This includes the following resources: